System and method for antenna diversity using equal power joint maximal ratio combining

- IPR Licensing, Inc.

An equal gain composite beamforming technique which includes the constraint that the power of the signal output by each antenna is the same, and is equal to the total power of the transmit signal divided by the number N of transmit antennas from which the signal is to be transmitted. By reducing output power requirements for each power amplifier, the silicon area of the power amplifiers are reduced by as much as N times (where N is equal to the number of transmit antennas) relative to a non-equal gain composite beamforming technique.

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Description

This application is a continuation of U.S. application Ser. No. 10/800,610, filed Mar. 15, 2004, which is a continuation of U.S. application Ser. No. 10/174,689, filed Jun. 19, 2002, pending, which in turn claims priority to U.S. Provisional Application No. 60/361,055, filed Mar. 1, 2002, to U.S. Provisional Application No. 60/365,797 filed Mar. 21, 2002, and to U.S. Provisional Application No. 60/380,139, filed May 6, 2002. The entirety of each of the aforementioned applications are incorporated herein by reference.This application is a reissue application of U.S. patent application Ser. No. 11/879,156 filed Jul. 16, 2007, which issued as U.S. Pat. No. 7,881,674 on Feb. 1, 2011, which is a continuation of U.S. patent application Ser. No. 10/800,610 filed Mar. 15, 2004, which issued as U.S. Pat. No. 7,245,881 on Jul. 17, 2007, which is a continuation of U.S. patent application Ser. No. 10/174,689 filed Jun. 19, 2002, which issued as U.S. Pat. No. 6,785,520 on Aug. 31, 2004, which claims the benefit of U.S. Provisional Application Ser. No. 60/361,055 filed Mar. 1, 2002, U.S. Provisional Application Ser. No. 60/365,797 filed Mar. 21, 2002, and U.S. Provisional Application Ser. No. 60/380,139 filed May 6, 2002, the contents of which are hereby incorporated by reference herein.

BACKGROUND OF THE INVENTION

The present invention is directed to an antenna (spatial) processing useful in wireless communication applications, such as short-range wireless applications.

Composite Beamforming (CBF) is an antenna processing technique in which a first communication device, having a plurality of antennas, weights a signal to be transmitted by its antennas to a second communication device also having a plurality of antennas. Similarly, the second communication device weights and combines the received signals received by its antennas. A multiple-input/multiple-output (MIMO) optimized communication system is defined by CBF. The transmit weights and receive weights are determined to optimize the link margin between the devices, thereby significantly extending the range of communication between the two communication devices. Techniques related to composite beamforming are the subject matter of above-identified commonly assigned co-pending application.

There is room for still further enhancing this CBF technique to optimize cost and implementation issues at the expense of only slight degradation in performance. Such a solution is extremely valuable in manufacturing a cost-effective integrated circuit solution.

SUMMARY OF THE INVENTION

An equal gain composite beamforming technique is provided that adds the constraint that the power of the signal output by each of the plurality of transmit antennas is the same, and is equal to the total power of the transmit signal divided by the number N of transmit antennas from which the signal is to be transmitted. This reduces output power requirements at each antenna. By reducing output power requirements for each power amplifier, the silicon area of the power amplifiers are reduced by as much as N times (where N is the number of transmit antennas) relative to non-equal gain CBF. Many implementation advantages are achieved by equal gain CBF, including savings in silicon, power requirements, etc.

The above and other objects and advantages will become more readily apparent when reference is made to the following description taken in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of two communication devices performing equal gain composite beamforming.

FIG. 2 shows frequency dependent weights for two antennas that are frequency shaped, but not equal gain.

FIG. 3 shows equal gain frequency dependent weights for two antennas.

FIG. 4 is a block diagram of a communication device capable of performing equal gain composite beamforming.

FIG. 5 is a flow diagram showing an adaptive algorithm to obtain equal gain transmit antenna weights for first and second communication devices in communication with each other.

FIG.6 FIG. 6 is a graphical diagram illustrating convergence of the adaptive algorithm shown in FIG. 5.

FIG. 7 is a graphical diagram illustrating a performance comparison between equal gain composite beamforming and non-equal gain composite beamforming.

FIG. 8 is a block diagram of a composite beamforming transmission process for a multi-carrier baseband modulation scheme.

FIG. 9 is a block diagram of a composite beamforming reception process for a multi-carrier baseband modulation scheme.

FIG. 10 is a block diagram of a composite beamforming transmission process for a single carrier baseband modulation scheme.

FIG. 11 is a block diagram of a composite beamforming reception process for a single carrier baseband modulation scheme.

FIG. 12 is a flow diagram for a process that is useful when one device on the communication link is composite beamforming capable and the other device uses antenna selection diversity capable.

DETAILED DESCRIPTION OF THE DRAWINGS

Referring first to FIG. 1, a system 10 is shown in which a first communication device and a second communication device 200 communicate with each other using radio frequency (RF) communication techniques. The devices use composite beamforming techniques when communicating with each other. In particular, communication device 100 has N plurality of antennas 110 and communication device 200 has M plurality of antennas 210. According to the composite beamforming (CBF) technique also described in the aforementioned co-pending application filed on even date, when communication device 100 transmits a signal to communication device 200, it applies to (i.e., multiplies or scales) a baseband signal s to be transmitted a transmit weight vector associated with a particular destination device, e.g., communication device 200, denoted wtx,1. Similarly, when communication device 200 transmits a baseband signal s to communication device 100, it multiplies the baseband signal s by a transmit weight vector wtx,2, associated with destination communication device 100. The (M×N) frequency dependent channel matrix from the N plurality of antennas of the first communication device 100 to M plurality of antennas of the second communication device 200 is H(k), and the frequency dependent communication channel (N×M) matrix between the M plurality of antennas of the second communication device and the N plurality of antennas of the first communication device is HT(k).

The transmit weight vectors wtx,1 and wtx2 wtx,2 each comprises a plurality of transmit weights corresponding to each of the N and M antennas, respectively. Each transmit weight is a complex quantity. Moreover, each transmit weight vector is frequency dependent; it may vary across the bandwidth of the baseband signal s to be transmitted. For example, if the baseband signal s is a multi-carrier signal of K sub-carriers, each transmit weight for a corresponding antenna varies across the K sub-carriers. Similarly, if the baseband signal s is a single-carrier signal (that can be divided or synthesized into K frequency sub-bands), each transmit weight for a corresponding antenna varies across the bandwidth of the baseband signal. Therefore, the transmit weight vector is dependent on frequency, or varies with frequency sub-band/sub-carrier k, such that wtx becomes wtx(f), or more commonly referred to as wtx(k), where k is the frequency sub-band/sub-carrier index.

While the terms frequency sub-band/sub-carrier are used herein in connection with beamforming in a frequency dependent channel, it should be understood that the term “sub-band” is meant to include a narrow bandwidth of spectrum forming a part of a baseband signal. The sub-band may be a single discrete frequency (within a suitable frequency resolution that a device can process) or a narrow bandwidth of several frequencies.

The receiving communication device also weights the signals received at its antennas with a receive antenna weight vector wrx(k). Communication device 100 uses a receive antenna weight vector wrx,1(k) when receiving a transmission from communication device 200, and communication device 200 uses a receive antenna weight vector wrx,2(k) when receiving a transmission from communication device 100. The receive antenna weights of each vector are matched to the received signals by the receiving communication device. The receive weight vector may also be frequency dependent.

Generally, transmit weight vector wtx,1 comprises a plurality of transmit antenna weights wtx,1,i1,i(k)eiφ1,i,(k), where β1,i(k) is the magnitude of the antenna weight, φ1,i,(k) is the phase of the antenna weight, i is the antenna index, and k is the frequency sub-band or sub-carrier index (up to K frequency sub-bands/sub-carriers). The subscripts tx,1 denote that it is a vector that communication device 100 uses to transmit to communication device 2. Similarly, the subscripts tx,2 denote that it is a vector that communication device 200 uses to transmit to communication device 100.

Under the constraint of an equal gain composite beamforming (EGCBF) process, the power of the transmit signal output by each transmit antenna is the same, and is equal to the total power associated with the transmit signal (Ptx) divided by the number of transmit antennas. Thus, for communication device 100, that is Ptx/N. For communication device 200, that is Ptx/M. Consequently, each power amplifier associated with an antenna need only support 1/N of the total output power. Example: For N=4, Ptx=17 dBm, each power amplifier need only support a max linear output power of 17−10log(4)=11 dBm. Thus, whereas for non-equal gain composite beamforming each power amplifier must support to the total transmit power, such is not the case for equal gain beamforming. The equal-gain constraint makes the power amplifier design much simpler. Equal gain CBF performs very close to non-equal gain CBF (within 1-2 dB), but costs significantly less to implement in terms of power amplifier requirements and affords the opportunity to deploy the power amplifiers on the same silicon integrated circuit as the RF circuitry.

When considering a frequency dependent communication channel, the EGCBF constraint implies that for each and every antenna i, the sum of the power |wtx,i (k)|2 of the antenna signal across all of frequencies of the baseband signal (the frequency sub-bands or sub-carrier frequencies k=1 to K) is equal to Ptx/N. This is the equal gain constraint applied to a frequency dependent channel represented by K sub-carrier frequencies or frequency sub-bands.

An additional constraint can be imposed on the frequency dependent equal gain constraint explained above. This additional constraint is a frequency shaping constraint which requires that at each frequency of the baseband signal to be transmitted (e.g., frequency sub-band or frequency sub-carrier k), the sum of the power of signals across all of the transmit antennas (|wtx,i (k)|2 for i=1 to N) is equal to Ptx/K. This constraint is useful to ensure that, in an iterative process between two communication devices, the transmit weights of the two devices will converge to optimal values. An additional benefit of this constraint is that the transmitting device can easily satisfy spectral mask requirements of a communication standard, such as IEEE 802.11x.

One solution to a system that combines the frequency selective equal gain constraint and the frequency shaping constraint is that |wtx,i (k)|2=Ptx/(KN). This solution says that the magnitude of each transmit antenna weight is Ptx/(KN). If the transmit weight vector is normalized to unity, i.e., divided by [Ptx/(KN)]1/2, then the vectors for all of the antennas across all of the k frequency sub-bands becomes a N×K matrix of phase values eiφik, where i is the antenna index and k is the sub-band/sub-carrier index.

11 21 31 N 1 12 N 2 13 N 3 1 K 2 K 3 K NK

FIG. 2 shows the magnitude of the antenna weights in a 2-antenna example that satisfy the frequency shaping constraint but not the equal gain constraint. The magnitude of the antenna weights for the two antennas at each of three exemplary frequency sub-bands (k, k+1, k+2) are shown. The sum of the magnitude of the antenna weights of both antennas at any of the frequency sub-bands shown adds to a constant value, Ptx/K.

FIG. 3 shows the magnitude of the antenna weights in the 2-antenna example that satisfy the equal gain constraint and the frequency shaping constraint. In this example, the total power at antenna 1 (i.e., the total area under the weight curve across k frequency sub-bands) is P/2 (N=2 in the example) and the total power of the antennas at any frequency sub-band k is P/K. Thus, the power or magnitude of the transmit antenna weight for any given antenna is equal (constant) across the bandwidth of the baseband signal, and is equal to P/(KN) for all k. In other words, at each antenna, the power is equally distributed across the bandwidth of the baseband signal.

For EGCBF, the optimization problem becomes

arg max { w tx .1 H ( k ) H H ( k ) H ( k ) w tx , 1 ( k ) } , subject to w tx . i ( k ) 2 = P tx / ( NK ) . ( 1 )

A closed-form solution to equation (1) is difficult to obtain since it requires the solution of a non-linear system of equations. However, the following necessary conditions for the solution to (1) have been derived and are given below:

Optimal wrx satisfies wrx=kHwtx for some nonzero constant k.

Optimal wtx satisfies Im(Λ*HHHe)=0, Λ=diag(eiφ0, eiφ1, . . . , eiφN-1), wtx=e=(eiφ0, eiφ1, . . . , eiφN-1)T. One solution to equation (1) is an adaptive algorithm for EGCBF. Although the algorithm is not necessarily optimal in terms of solving equation (1), it is simple to implement and simulations have verified that it converges reliably at the expense of only a 1-2 dB performance penalty relative to non-equal gain CBF. This adaptive algorithm is described hereinafter in conjunction with FIG. 5.

The communication devices at both ends of the link , link, i.e., devices 100 and 200 may have any known suitable architecture to transmit, receive and process signals. An example of a communication device block diagram is shown in FIG. 4. The communication device 300 comprises an RF section 310, a baseband section 420 320 and optionally a host 330. There are a plurality of antennas, e.g., four antennas 302, 304, 306, 308 coupled to the RF section 310 that are used for transmission and reception. The device may have only two antennas. The RF section 310 has a transmitter (Tx) 312 that upconverts baseband signals for transmission, and a receiver (Rx) 314 that downconverts received RF signals for baseband processing. In the context of the composite beamforming techniques described herein, the Tx 312 upconverts and supplies separately weighted signals to corresponding ones of each of the plurality of antennas via separate power amplifiers for simultaneous transmission. Similarly, the Rx 314 downconverts and supplies received signals from each of the plurality of antennas to the baseband section 320. The baseband section 320 performs processing of baseband signals to recover the information from a received signal, and to convert information in preparation for transmission. The baseband section 320 may implement any of a variety of communication formats or standards, such as WLAN standards IEEE 802.11x, Bluetooth™, as well as other standards.

The intelligence to execute the computations for the composite beamforming techniques described herein may be implemented in a variety of ways. For example, a processor 322 in the baseband section 320 may execute instructions encoded on a processor readable memory 324 (RAM, ROM, EEPROM, etc.) that cause the processor 322 to perform the composite beamforming steps described herein. Alternatively, an application specific integrated circuit (ASIC) may be configured with the appropriate firmware, e.g., field programmable gates that implement digital signal processing instructions to perform the composite beamforming steps. This ASIC may be part of, or the entirety of, the baseband section 320. Still another alternative is for the beamforming computations to be performed by a host processor 332 (in the host 330) by executing instructions stored in (or encoded on) a processor readable memory 334. The RF section 310 may be embodied by one integrated circuit, and the baseband section 320 may be embodied by another integrated circuit. The communication device on each end of the communication link need not have the same device architecture or implementation.

Regardless of the specific implementation chosen, the composite beamforming process is generally performed as follows. A transmit weight vector (comprising a plurality of complex transmit antenna weights corresponding to the number of transmit antennas) is applied to, i.e., scaled or multiplied by, a baseband signal to be transmitted, and each resulting weighted signal is coupled to a transmitter where it is upconverted, amplified and coupled to a corresponding one of the transmit antennas for simultaneous transmission. At the communication device on the other end of the link, the transmit signals are detected at each of the plurality of antennas and downconverted to a baseband signal. Each baseband signal is multiplied by a corresponding one of the complex receive antenna weights and combined to form a resulting receive signal. The architecture of the RF section necessary to accommodate the beamforming techniques described herein may vary with a particular RF design, and many are known in the art and thus is not described herein.

With reference to FIG. 5, an adaptive procedure 400 for determining near optimum transmit antenna weight vectors for first and second communication devices will be described. The antenna weight parameters in FIG. 4 are written with indexes to reflect communication between a WLAN access point (AP) and a station (STA), but without loss of generality, it should be understood that this process is not limited to WLAN application, but is useful in any short-range wireless application. The AP has Nap antennas and the STA has Nsta antennas. Assuming the AP begins with a transmission to the STA, the initial AP transmit weight vector wT,AP,0(k) is [1,1, . . . 1], equal gain and normalized by 1/(Nap)1/2 for all antennas and all frequency sub-bands/sub-carriers k. Phase for the transmit antenna weights is also initially set to zero. The index T indicates it is a transmit weight vector, index AP indicates it is an AP vector, index 0 is the iteration of the vector, and (k) indicates that it is frequency sub-band/sub-carrier dependent. The index i is the antenna index. The transmit weight vectors identified in FIG. 5 form an N x K matrix explained above.

In step 410, a baseband signal is scaled by the initial AP transmit weight vector wT,A,P,0(k), upconverted and transmitted to the STA. The transmitted signal is altered by the frequency dependent channel matrix H(k) from AP-STA. The STA receives the signal and matches its initial receive weight vector wR,STA,0(k) to the signals received at its antennas. In step 420, the STA gain normalizes the receive weight vector wR,STA,0(k) and computes the conjugate of gain-normalized receive weight vector to generate the STA's initial transmit weights for transmitting a signal back to the AP. The STA scales the signal to be transmitted to the AP by the initial transmit weight vector, upconverts that signal and transmits it to the AP. Computing the conjugate for the gain-normalized vector means essentially co-phasing the receive weight vector (i.e., phase conjugating the receive weight vector). The transmitted signal is effectively scaled by the frequency dependent channel matrix HT(k). At the AP, the receive weight vector is matched to the signals received at its antennas. The AP then computes the conjugate of the gain-normalized receive weight vector as the next transmit weight vector wT,AP,1(k) and in step 430 transmits a signal to the STA with that transmit weight vector. The STA receives the signal transmitted from the AP with this next transmit weight vector and matches to the received signals to compute a next receive weight vector wR,STA,1(k). Again, the STA computes the conjugate of the gain-normalized receive weight vector wR,STA,1(k) as its next transmit weight vector wT,STA,1(k) for transmitting a signal back to the AP. This process repeats for several iterations, ultimately converging to transmit weight vectors that achieve nearly the same performance as non-equal gain composite beamforming. This adaptive process works even if one of the devices, such as a STA, has a single antenna for transmission and reception. In addition, throughout the adaptive process, the frequency shaped constraint may be maintained so that for each antenna, the transmit antenna weight is constant across the bandwidth of the baseband signal.

FIG. 6 shows that the adaptive algorithm converges to performance loss that is less than 1 dB with 95% probability after 3-4 iterations. FIG. 7 shows simulation results that indicate that the performance degradation compared to the non-equal gain composite beamforming case is only 1-2 dB.

Each communication device stores the transmit antenna weights determined to most effectively communicate with each of the other communication devices that it may communicate with. The transmit antenna weights may be determined according to the adaptive algorithm described above. When storing the transmit weights of a transmit weight vector, in order to conserve memory space in the communication device, the device may store, for each antenna, weights for a subset or a portion of the total number of weights that span the bandwidth of the baseband signal. For example, if there are K weights for K frequency sub-bands or sub-carrier frequencies, only a sampling of those weights are actually stored, such as weights for every other, every third, every fourth, etc., k sub-band or sub-carrier. Then, the stored subset of transmit weights are retrieved from storage when a device is to commence transmission of a signal, and the remaining weights are generated by interpolation from the stored subset of weights. Any suitable interpolation can be used, such as linear interpolation, to obtain the complete set of weights across the K sub-bands or sub-carriers for each antenna.

With reference to FIG. 8, a beamforming transmission process 500 is shown for a multi-carrier baseband modulation scheme. For a multi-carrier modulation system, such as an orthogonal frequency division multiplexed (OFDM) system used in IEEE 802.11a, the data symbols are in the frequency domain. K symbols are assigned to K sub-carriers (K=52 for 802.11a). For convenience, each of the transmit antenna weights are described as a function of (k), the sub-carrier frequency. The equal gain transmit antenna weights are computed by any of the processes described herein at each of the sub-carrier frequencies. There is a signal processing path for each of the N antennas. In each signal processing path, a multiplier 510 multiplies the frequency domain symbol s(k) by the corresponding equal-gain transmit antenna weight wtx(k) and because wtx(k) has K values, there are K results from the multiplication process. The results are stored in a buffer 520 for k=1 to K. An inverse Fast Fourier Transform (IFFT) 530 is coupled to the buffer to convert the frequency domain results stored in buffer 520 to a digital time domain signal for each of the K sub-carriers. There may be some adjustment made for cyclic prefixes caused by the OFDM process. A filter 540 provides lowpass filtering of the result of the IFFT process. The digital results of the filtering process are converted to analog signals by a D/A 550. The outputs of the D/A 550 are coupled to RF circuitry 560 that upconverts the analog signals to the appropriate RF signal which is coupled via a power amplifier (PA) 570 to one of the N antennas 580. In this manner, for each antenna 580, the signal s(k) is multiplied by respective transmit antenna weights whose phase values may vary as a function of the sub-carrier frequency k.

FIG. 9 shows a reception process 600 that is essentially the inverse of the transmission process 500 shown in FIG. 8. There is a signal processing channel for each of the antennas 580. RF circuitry 610 downconverts the RF signals detected at each antenna 580 for each of the sub-carriers. An A/D 620 converts the analog signal to a digital signal. A lowpass filter 630 filters the digital signal. There may be some adjustment made for cyclic prefixes caused by the OFDM process. A buffer 640 stores the time domain digital signal in slots associated with each sub-carrier frequency k. An FFT 650 converts the time domain digital signal in buffer 640 to a frequency domain signal corresponding to each sub-carrier frequency k. The output of the FFT 650 is coupled to a multiplier 660 that multiplies the digital signal for each sub-carrier k by a corresponding receive antenna weight wrx(k) for the corresponding one of the N antennas. The outputs of each of the multipliers 660 are combined by an adder 670 to recover the digital frequency domain symbol s(k). The signal s(k) is then mapped back to symbol b(k).

FIGS. 10 and 11 show transmission and reception processes, respectively, that are applicable to a single-carrier baseband modulation scheme, such as that used by the IEEE 802.11b standard. The data symbols in such a system are m the time domain. FIG. 10 shows a beamforming transmission process 700. Since in a frequency dependent channel, the transmit antenna weights are frequency dependent, the passband of the time-domain baseband signal is synthesized into frequency bins or sub-bands (K bins or sub-bands) and equal gain transmit beamforming weights are computed for each frequency bin using any of the processes described herein. There are processing channels for each antenna. In each processing channel, transmit filters 710 are synthesized with the frequency response specified by the beamforming weights. Thus, each transmit filter 710 has a frequency response defined by the transmit antenna weight wtx(f) associated with that antenna. The data symbol s(n) is passed through the transmit filter 710 which in effect applies the frequency dependent antenna weight wtx(f) to the data symbol s(n). The D/A 720 converts the digital output of the transmit filter 710 to an analog signal. The RF circuitry 730 upconverts the analog signal and couples the upconverted analog signal to an antenna 750 via a power amplifier 740.

FIG. 11 shows a reception process 800 suitable for a single carrier system. There is a processing channel for each antenna 750. In each processing channel, RF circuitry 810 downconverts the received RF signal. An A/D 820 converts the downconverted analog signal to a digital signal. Like the frequency dependent transmit antenna weights, the receive antenna weights are computed for the plurality of frequency sub-bands. Receive filters 830 are synthesized with the frequency response specified by the frequency dependent receive beamforming weights wrx(f) and the received digital signal is passed through filters 830 for each antenna, effectively applying a frequency dependent antenna weight to the received signal for each antenna. The results of the filters 830 are combined in an adder 850, and then passed to a demodulator 860 for demodulation.

FIG. 12 shows a procedure for use when only one of the two devices supports beamforming. For example, N-CBF is supported at a first communication device (an AP) but not at a second communication device (a STA). In this case, the STA is likely to support 2-antenna Tx/Rx selection diversity as discussed previously. If this is the case, it is possible for the AP to achieve 3 dB better performance than Nth order maximal ratio combining (MRC) at both ends of the link.

When a STA associates or whenever a significant change in channel response is detected, the AP sends a special training sequence to help the STA select the best of its two antennas. The training sequence uses messages entirely supported by the applicable media access control protocol, which in the following example is IEEE 802.11x.

The sequence consists of 2 MSDUs (ideally containing data that is actually meant for the STA so as not to incur a loss in throughput). In step 900, the AP sends the first MSDU using a Tx weight vector having equal gain orthogonal transmit weights (also optionally frequency shaped). For example, if the number of AP antennas is 4, the transmit weight vector is [1 1 1 1]T. In step 910, the 2-antenna selection diversity STA responds by transmitting a message using one of its' its two antennas; the antenna that best received the signal from the AP. The AP decodes the message from the STA, and obtains one row of the H matrix (such as the first row hr1). In step 920, the AP sends the second MSDU using a frequency dependent transmit weight vector which is orthogonal to the first row of H (determined in step 610 910), and equal-gain normalized such that the magnitude of the signals at each antenna is equal to P/N. In addition, the transmit weight vector may be frequency shaped across so that at each frequency of the baseband signal, the sum of the power output by the antennas of the first communication device is constant across. When the STA receives the second MSDU, it forces the STA to transmit a response message in step 630 930 using the other antenna, allowing the AP to see the second row of the H matrix, such as hr2. Now the AP knows the entire H matrix. The AP then decides which row of the H matrix will provide “better” MRC at the STA by computing a norm of each row, hr1 and hr2, of the H matrix and, and selecting the row that has the greater norm as the frequency dependent transmit weight vector for further transmissions to that STA until another change is detected in the channel. The row that is selected is equal gain normalized before it is used for transmitting to that STA.

Equal gain composite beamforming provides significant advantages. By reducing output power requirements for each power amplifier, the silicon area of the power amplifiers are reduced by as much as N times (where N is equal to the number of antennas) relative to non-equal gain CBF. The silicon area savings translates into a cost savings due to (1) less silicon area, and (2) the ability to integrate the power amplifiers onto the same die (perhaps even the same die as the radio frequency transceiver itself).

The efficiency (efficiency being defined as the output power divided by DC current consumption) for each power amplifier is N times larger in the EGCBF case than in the non-equal gain CBF case. With EGCBF, the same output power as non-equal CBF is achieved with N times less DC current.

Equal gain CBF reduces power requirements for each of the power amplifiers, which in turn increases the output impedance of each of the power amplifiers (since impedance is inversely proportional to current, and supply current requirements will be reduced). When the output impedance of the power amplifier is increased, the matching networks required for the power amplifiers are greatly simplified and require less silicon area. Moreover, reducing power requirements for the individual power amplifiers provides greater flexibility for systems with low supply voltage.

To summarize, a method is provided that accomplishes applying a transmit weight vector to a baseband signal to be transmitted from the first communication device to the second communication device, the transmit weight vector comprising a complex transmit antenna weight for each of N plurality of antennas of the first communication device, wherein each complex transmit antenna weight has a magnitude and a phase whose values may vary with frequency across a bandwidth of the baseband signal, thereby generating N transmit signals each of which is weighted across the bandwidth of the baseband signal, wherein the magnitude of the complex transmit antenna weight associated with each antenna is such that the power to be output at each antenna is the same and is equal to the total power to be output by all of the N antennas divided by N; receiving at the N plurality of antennas of the first communication device a signal that was transmitted by the second communication device; determining a receive weight vector comprising a plurality of complex receive antenna weights for the N plurality of antennas of the first communication device from the signals received by the N plurality of antennas, wherein each receive antenna weight has a magnitude and a phase whose values may vary with frequency; and updating the transmit weight vector for the N plurality of antennas of the first communication device for transmitting signals to the second communication device by gain normalizing the receive weight vector and computing a conjugate thereof. This process may be performed such that at substantially all frequencies of the baseband signal, the sum of the magnitude of the complex transmit antenna weights across the plurality of antennas of the first communication device is constant. Moreover, where the bandwidth of the baseband signal comprises K plurality of frequency sub-bands, the magnitude of the complex transmit antenna weights associated with each of the N plurality of antennas is such that the power to be output by each antenna is the same and is equal to 1/(KN) of the total power to be output for all of the K frequency sub-bands. This process may be embodied by instructions encoded on a medium or in a communication device.

In addition, a method is provided that accomplishes a method for communicating signals from a first communication device to a second communication device using radio frequency (RF) communication techniques, comprising: applying to a first signal to be transmitted from the first communication device to the second communication device a transmit weight vector, the transmit weight vector comprising a complex transmit antenna weight for each of the N plurality of antennas, wherein each complex transmit antenna weight has a magnitude and a phase whose values may vary with frequency across a bandwidth of the baseband signal, thereby generating N transmit signals each of which is weighted across the bandwidth of the baseband signal, wherein the magnitude of the complex transmit antenna weights associated with each antenna is such that the power to be output at each antenna is the same and is equal to the total power to be output by all of the N antennas divided by N; from a first response signal at the plurality of antennas of the first communication device transmitted from a first of two antennas of the second communication device, deriving a first row of a channel response matrix that describes the channel response between the first communication device and the second communication device; applying to a second signal for transmission by the plurality of antennas of the first communication device a transmit weight vector that is orthogonal to the first row of the channel response matrix, and wherein the transmit weight vector comprises a plurality of complex transmit antenna weights, wherein each complex transmit antenna weight has a magnitude and a phase whose values may vary with frequency across a bandwidth of the second signal, thereby generating N transmit signals each of which is weighted across the bandwidth of the baseband signal, wherein the magnitude of the complex transmit antenna weights associated with each antenna is such that the power to be output at each antenna is the same and is equal to the total power to be output by all of the N antennas divided by N; deriving a second row of the channel response matrix from a second response signal received from a second of the two antennas of the second communication device; and selecting one of the first and second rows of the channel response matrix that provides better signal-to-noise at the second communication device as the transmit weight vector for further transmission of signals to the second communication device. This process may be performed such that at substantially all frequencies of the baseband signal, the sum of the magnitude of the complex transmit antenna weights across the plurality of antennas of the first communication device is constant. Moreover, where the bandwidth of the baseband signal comprises K plurality of frequency sub-bands, the magnitude of the complex transmit antenna weights associated with each of the N plurality of antennas is such that the power to be output by each antenna is the same and is equal to 1/(KN) of the total power to be output for all of the K frequency sub-bands. This process may be embodied by instructions encoded on a medium or in a communication device.

The above description is intended by way of example only.

Claims

1. A wireless communication device, comprising:

a plurality of N antennas; and
a baseband processor configured to determine a receive weight vector of a plurality of complex receive antenna weights for each of the plurality of N antennas, the receive antenna weights applied to a received baseband signal;
compute a transmit weight vector by computing a conjugate of the receive weight vector, the transmit weight vector comprising a complex transmit antenna weight for each of plurality of N antennas of the communication device, wherein each complex transmit antenna weight has a magnitude and a phase whose values may vary with frequency across a bandwidth of the baseband signal, thereby generating a plurality of N transmit signals each of which is weighted across the bandwidth of the baseband signal to be transmitted from corresponding ones of the plurality of N antennas to a second communication device, wherein the magnitude of the complex transmit antenna weight associated with each antenna is such that the power to be output at each antenna is the same and is equal to the total power to be output by all of the N antennas divided by N and such that the sum of the power at each corresponding frequency across the plurality of transmit signals is equal to a constant;
apply the transmit weight vector to a baseband signal for transmission via the plurality of N antennas; and
update the transmit weight vector by repeating the determining of the receive weight vector and computing of the transmit weight vector each time signals are received to update the transmit weight vector.

2. The device of claim 1, wherein the bandwidth of the baseband signal comprises K plurality of frequency sub-bands, and the magnitude of the complex transmit antenna weights associated with each of the plurality of N antennas is such that the power to be output by each antenna is the same and is equal to 1/(KN) of the total power to be output for all of the K frequency sub-bands of the communication device.

3. The device of claim 2, further comprising a baseband memory configured to store, for each of the N antennas, complex transmit antenna weights for a subset of the K frequency sub-bands or sub-carriers.

4. The device of claim 3, wherein the baseband processor and the stored subset of complex transmit antenna N and weights generate therefrom the complete set of antenna weights for all of the K frequency sub-bands or sub-carriers using interpolation techniques.

5. The device of claim 1, wherein the receive weight vector, the transmit weight vector and the baseband signal of the are applied to each of K frequency sub-bands of the baseband signal that correspond to sub-carriers of a multi-carrier baseband signal or synthesized frequency sub-bands of a single carrier baseband signal.

6. A wireless communication device comprising:

a plurality of N antennas; and
a processor configured to produce a weight for each of the plurality of N antennas for use in beamforming; wherein the processor is further configured to determine a total transmit power; wherein the processor is configured to divide the total transmit power by N; wherein the processor is further configured to produce a multi-carrier signal for transmission; wherein the multi-carrier signal is weighted for each antenna per the produced weight and a power applied to each of the N antennas for the weighted multi-carrier signal is equal to the total transmit power divided by N.

7. The wireless communication device of claim 6 wherein the beamforming is used for multiple input multiple output.

8. The wireless communication device of claim 6 wherein the multi-carrier signal is an orthogonal frequency division multiplex signal.

9. The wireless communication device of claim 6 wherein the multi-carrier signal has a plurality of K subcarriers; wherein a power applied to each of the K subcarriers per antenna is equal to the total transmit power divided by KN.

10. A method comprising:

producing, by a wireless communication device, a weight for each of a plurality of N antennas for use in beamforming;
determining, by the wireless communication device, a total transmit power;
dividing, by the wireless communication device, the total transmit power by N;
producing, by the wireless communication device, a multi-carrier signal for transmission;
weighting, by the wireless communication device, the multi-carrier signal for each antenna per the produced weight; and
applying, by the wireless communication device, a power to each of the N antennas so that the weighted multi-carrier signal for that antenna is equal to the total transmit power divided by N.

11. The method of claim 10 wherein the beamforming is used for multiple input multiple output.

12. The method of claim 10 wherein the multi-carrier signal is an orthogonal frequency division multiplex signal.

13. The method of claim 10 wherein the multi-carrier signal has a plurality of K subcarriers; wherein a power applied to each of the K subcarriers per antenna is equal to the total transmit power divided by KN.

Referenced Cited
U.S. Patent Documents
4121221 October 17, 1978 Meadows
4599734 July 8, 1986 Yamamoto
4639914 January 27, 1987 Winters
4811420 March 7, 1989 Avis et al.
5274844 December 28, 1993 Harrison et al.
5394435 February 28, 1995 Weerackody
5414699 May 9, 1995 Lee
5437055 July 25, 1995 Wheatley, III
5457808 October 10, 1995 Osawa et al.
5491723 February 13, 1996 Diepstraten
5493307 February 20, 1996 Tsujimoto
5493722 February 20, 1996 Gunn et al.
5507035 April 9, 1996 Bantz et al.
5539832 July 23, 1996 Weinstein et al.
5570366 October 29, 1996 Baker et al.
5577265 November 19, 1996 Wheatley, III
5610617 March 11, 1997 Gans et al.
5621732 April 15, 1997 Osawa
5752173 May 12, 1998 Tsujimoto
5761193 June 2, 1998 Derango et al.
5761237 June 2, 1998 Petersen et al.
5771462 June 23, 1998 Olsen
5812531 September 22, 1998 Cheung et al.
5848105 December 8, 1998 Gardner et al.
5854611 December 29, 1998 Gans et al.
5898679 April 27, 1999 Brederveld et al.
5912921 June 15, 1999 Warren et al.
5924020 July 13, 1999 Forssen et al.
5930248 July 27, 1999 Langlet et al.
5982327 November 9, 1999 Vook et al.
5999826 December 7, 1999 Whinnett
6008760 December 28, 1999 Shattil
6018642 January 25, 2000 Adachi
6023625 February 8, 2000 Myers, Jr.
6037898 March 14, 2000 Parish et al.
6038272 March 14, 2000 Golden et al.
6044120 March 28, 2000 Bar-David et al.
6058105 May 2, 2000 Hochwald et al.
6064338 May 16, 2000 Kobayakawa et al.
6091934 July 18, 2000 Berman et al.
6097771 August 1, 2000 Foschini
6118788 September 12, 2000 Kermani
6122260 September 19, 2000 Liu et al.
6124824 September 26, 2000 Xu et al.
6141393 October 31, 2000 Thomas et al.
6141567 October 31, 2000 Youssefmir et al.
6144651 November 7, 2000 Rinchiuso et al.
6144711 November 7, 2000 Raleigh et al.
6147985 November 14, 2000 Bar-David et al.
6157340 December 5, 2000 Xu et al.
6157843 December 5, 2000 Derango et al.
6177906 January 23, 2001 Petrus
6185440 February 6, 2001 Barratt et al.
6195045 February 27, 2001 Xu et al.
6211671 April 3, 2001 Shattil
6218986 April 17, 2001 Yukitomo et al.
6249250 June 19, 2001 Namekata et al.
6252548 June 26, 2001 Jeon
6252884 June 26, 2001 Hunter
6266528 July 24, 2001 Farzaneh
6295026 September 25, 2001 Chen et al.
6298092 October 2, 2001 Heath, Jr.
6307882 October 23, 2001 Marzetta
6317466 November 13, 2001 Foschini et al.
6327310 December 4, 2001 Hochwald et al.
6331837 December 18, 2001 Shattil
6349219 February 19, 2002 Hochwald et al.
6351499 February 26, 2002 Paulraj et al.
6362781 March 26, 2002 Thomas et al.
6369758 April 9, 2002 Zhang
6370182 April 9, 2002 Bierly et al.
6377631 April 23, 2002 Raleigh
6377636 April 23, 2002 Paulraj et al.
6377819 April 23, 2002 Gesbert et al.
6389056 May 14, 2002 Kanterakis et al.
6400699 June 4, 2002 Airy et al.
6400780 June 4, 2002 Rashid-Farrokhi et al.
6442214 August 27, 2002 Boleskei et al.
6462709 October 8, 2002 Choi
6463295 October 8, 2002 Yun
6473467 October 29, 2002 Wallace et al.
6522898 February 18, 2003 Kohno et al.
6549786 April 15, 2003 Cheung
6560299 May 6, 2003 Strolle et al.
6570929 May 27, 2003 Eriksson
6584161 June 24, 2003 Hottinen et al.
6625162 September 23, 2003 Myojo et al.
6636568 October 21, 2003 Kadous
6646600 November 11, 2003 Vail et al.
6684064 January 27, 2004 Kazakevich et al.
6687492 February 3, 2004 Sugar et al.
6728294 April 27, 2004 Kohno et al.
6728517 April 27, 2004 Sugar et al.
6771989 August 3, 2004 Katz et al.
6792033 September 14, 2004 Maruta et al.
6862271 March 1, 2005 Medvedev et al.
6873606 March 29, 2005 Agrawal et al.
6873651 March 29, 2005 Tesfai et al.
6888878 May 3, 2005 Prysby et al.
6895255 May 17, 2005 Bridgelall
6901122 May 31, 2005 Nadgauda et al.
6904021 June 7, 2005 Belcea
6940917 September 6, 2005 Menon et al.
6956907 October 18, 2005 Ketchum
6961545 November 1, 2005 Tehrani et al.
6963742 November 8, 2005 Boros et al.
6970682 November 29, 2005 Crilly, Jr. et al.
6980600 December 27, 2005 Ratnarajah
6983167 January 3, 2006 Adachi et al.
7027536 April 11, 2006 Al-Dhahir
7031368 April 18, 2006 Maruta et al.
7042860 May 9, 2006 Kasami et al.
7155231 December 26, 2006 Burke et al.
7224758 May 29, 2007 Banister
7224942 May 29, 2007 Dent
7230940 June 12, 2007 Fantaske
7277409 October 2, 2007 Thermond et al.
7299071 November 20, 2007 Barratt et al.
7340279 March 4, 2008 Chen et al.
7342875 March 11, 2008 Hammons et al.
7570921 August 4, 2009 Sugar et al.
7573945 August 11, 2009 Tesfai et al.
7805167 September 28, 2010 Esmailzadeh
8224263 July 17, 2012 Nogami et al.
20010012764 August 9, 2001 Edwards et al.
20010015994 August 23, 2001 Nam
20010046255 November 29, 2001 Shattil
20010053143 December 20, 2001 Li et al.
20010053699 December 20, 2001 McCrady et al.
20020001316 January 3, 2002 Hornsby et al.
20020024975 February 28, 2002 Hendler
20020034191 March 21, 2002 Shattil
20020039884 April 4, 2002 Raynes et al.
20020045435 April 18, 2002 Fantaske
20020051430 May 2, 2002 Kasami et al.
20020064246 May 30, 2002 Kelkar et al.
20020067309 June 6, 2002 Baker et al.
20020072392 June 13, 2002 Awater et al.
20020085643 July 4, 2002 Kitchener et al.
20020102950 August 1, 2002 Gore et al.
20020111142 August 15, 2002 Klimovitch
20020118781 August 29, 2002 Thomas et al.
20020122383 September 5, 2002 Wu et al.
20020122501 September 5, 2002 Awater et al.
20020127978 September 12, 2002 Khatri
20020136170 September 26, 2002 Struhsaker
20020141355 October 3, 2002 Struhsaker et al.
20020147032 October 10, 2002 Yoon et al.
20020158801 October 31, 2002 Crilly, Jr. et al.
20020159537 October 31, 2002 Crilly, Jr. et al.
20020172186 November 21, 2002 Larsson
20020172269 November 21, 2002 Xu
20020196842 December 26, 2002 Onggosanusi et al.
20030002450 January 2, 2003 Jalali et al.
20030022693 January 30, 2003 Gerogiokas et al.
20030032423 February 13, 2003 Boros et al.
20030035491 February 20, 2003 Walton et al.
20030048761 March 13, 2003 Jarett
20030100324 May 29, 2003 Kasapi
20030108117 June 12, 2003 Ketchum et al.
20030114108 June 19, 2003 Frecassetti et al.
20030125090 July 3, 2003 Zeira
20030139194 July 24, 2003 Onggosanusi et al.
20030157954 August 21, 2003 Medvedev et al.
20030181165 September 25, 2003 Sugar et al.
20040072546 April 15, 2004 Sugar et al.
20040104839 June 3, 2004 Velazquez et al.
20050192048 September 1, 2005 Bridgelall
20070117513 May 24, 2007 Kasami et al.
Foreign Patent Documents
0 901 219 March 1999 EP
99/40648 August 1999 WO
99/57820 November 1999 WO
01/05061 January 2001 WO
01/45300 June 2001 WO
01/69800 September 2001 WO
02/03568 January 2002 WO
Other references
  • Aziz et al., “Indoor Throughput and Range Improvements Using Standard Complaint AP Antenna Diversity in IEEE 802.11a and ETSI HIPERLAN/2”, Vehicular Technology Conference, 2002, VTC 2001, Oct. 7-11, 2001, IEEE VTS 54th, vol. 4, pp. 2294-2298.
  • Brunner et al., “Downlink Beamforming for WCDMA Based on Uplink Channel Parameters”; Proceedings of 3rd European Personal Mobile Conference (EPMCC'99), Mar. 1999, pp. 375-380.
  • Choi et al., “MISO CDMA Transmission with Simplified Receiver for Wireless Communication Handsets”, IEEE Transactions on Communications, vol. 49, No. 5, May 2002.
  • Golden et al., “V-BLAST: A High Capacity Space-Time Architecture for the Rich-Scattering Wireless Channel”, Bell Laboratories, Lucent Technologies, Proc. Int'l Symposium on Advanced Radio Technologies, Boulder, CO, Sep. 10, 1998.
  • Golub et al., Matrix Computation, “7.3 Power Iterations”, The Johns Hopkins University Press, Second Edition, pp. 351, (1983).
  • Heath et al., “A Simple Scheme for Transmit Diversity Using Partial Channel Feedback”, Signals, Systems & Computers, Conference Record of the Thirty-Second Asilomar Conference, Nov. 1-4, 1998; vol. 2; pp. 1073-1078.
  • Junqiang et al., “Spatial Multiuser Access with MIMO Smart Antennas for OFDM Systems”, IEEE VTC 2001, Sep. 2001, pp. 1553-1557.
  • LAN MAN Standards Committee Of The IEEE Computer Society, “Information Technology—Telecommunications And Information Exchange Between Systems—Local And Metropolitan Area Networks—Specific Requirements—Part 11: Wireless LAN Medium Access Control (MAC) And Physical Layer (PHY) Specifications”, ANSI/IEEE Std 802.11, 1999 Edition (R2003), (Reaffirmed Jun. 12, 2003).
  • Lee et al., “Antenna Diversity for an OFDM System in a Fading Channel”, Proceeding of IEEE MILCOM 1999, Nov. 1999, pp. 1104-1109.
  • Meyer-Ottens, et al. “Downlink Beamforming for W-CDMA Using Feedback and Interference Estimate”, Mar. 9, 2001.
  • Panasonic et al., “Clairificatioin of SCH transmitted by TSTD,” 3GPP TSG RAN WG1 Meeting #15, R1-00-1080 (Aug. 22-25, 2000).
  • Perahia et al., “Adaptive Antenna Arrays and Equalization for Indoor Digital Radio,” IEEE International Conference on Communications, pp. 592-596 (Jun. 1996).
  • Raleigh et al., “Spatio-Temporal Coding for Wireless Communication”, IEEE Transactions on Communications, vol. 46, No. 3, Mar. 1998, pp. 357-366.
  • Sampath et al., “Joint Transmit And Receive Optimization For High Data Rate Wireless Communication Using Multiple Antennas”, Signals, Systems, and Computers, vol. 1, Oct. 1999.
  • Stridh et al., “Spatial Characterization of Indoor Radio Channel Measurements at 5 GHz”, SAM 2000, Mar. 2000, pp. 58-62.
  • Texas Instruments, “Delay diversity for the BCH of TDD,” TSG-RAN Working Group 1, TSGR1#7(99)b45 (Aug. 30-Sep. 3, 1999).
  • Wennström et al., “On The Optimality And Performance Of Transmit And Receive Space Diversity In MIMO Channels”, IEEE Seminar on Communications Systems from Concept to Implementations, (Dec. 12, 2001).
  • Yang et al., “Joint Transmitter—Receiver Optimization For Multi-Input Multi-Output Systems With Decision Feedback”, IEEE Transactions On Information Theory, vol. 40, No. 5, pp. 1334-1347, (Sep. 1994).
  • Bolckei et al., “On the Capacity of OFDM-Based Spatial Multiplexing Systems,” IEEE Transactions on Communications, vol. 50, No. 2, pp. 225-234 (Feb. 2002).
  • Dammann et al., “Standard Conformable Antenna Diversity Techniques for OFDM and its Application to the DVB-T System,” IEEE Global Telecommunications Conference, vol. 5, pp. 3100-3105 (Nov. 2001).
  • Palomar et al., “Capacity Results of Spatially Correlated Frequency-Selective MIMO Channels in UMTS,” IEEE 54th Vehicular Technology Conference, vol. 2, pp. 553-557 (Oct. 7, 2001).
  • “BLAST High-Level Overview”, Lucent Technologies, Jul. 18, 2000.
  • “Lucent's ‘BLAST’ Chips to Take Off in Wireless Market”, EETimes.com, Oct. 16, 2002.
  • Ariyavisitakul et al., “Optimum Space-Time Processors With Dispersive Interference—Unified Analysis And Required Filter Span”, 1999 IEEE International Conference on Communications, vol. 2, pp. 1244-1249, (1999).
  • Bablan et al., “Optimum Diversity Combining and Equalization in Digital Data Transmission with Applications to Cellular Mobile Radio—Part II: Numerical Results”; May 1992; IEEE Transactions on Communications, vol. 30, No. 5; pp. 895-907.
  • Briesemeister et al., “Role-Based Multicast in Highly Mobile but Sparsely Connect Ad-Hoc Networks”; First Annual Workshop on Mobile Ad Hoc Networking & Computing; pp. 45-50; Aug. 2000.
  • Chiu et al., “OFDM Receiver Design”, EE225C, Fall 2000, University of California, Berkeley.
  • Chizhik et al., “Keyholes, Correlations, and Capacities of Multielement Transmit and Receiver Antennas”, IEEE Transactions on Wireless Communications, vol. 1, No. 2, Apr. 2002, pp. 361-368.
  • Chuah et al., “Capacity of Multi-Antenna Array Systems in Indoor Wireless Environment”, Nov. 1998, IEEE Globecom.
  • Golden et al., “Detection Algorithm and Initial Laboratory Results Using V-Blast Space-Time Communication Architecture”, Electronic Letters, Jan. 7, 1999, vol. 35, No. 1.
  • Golden et al., “V-Blast: A High Capacity Space- Time Architecture for the Rich-Scattering Wireless Channel”, Bell Laboratories, Lucent Technologies, Proc. Int'l Symposium on Advanced Radio Technologies, Boulder, CO, Sep. 10, 1998.
  • Irmer et al., “MISO Concepts for Frequency-Selective Channels”, 2002 International Zurich Seminar on Broadband Communications Access, Feb. 19-21, 2002.
  • Iserte et al., “Iterative Algorithm for the Estimation of Distributed Sources Localization Parameters”, SSP 2001, 11th IEEE Workshop on Statistical Signal Processing, Aug. 2001.
  • Iserte et al., “Joint Beamforming Strategies in OFDM-MIMO Systems”, ICASSP 2002, IEEE International Conference on Acoustics, Speech and Signal Processing, May 2002.
  • Iserte et al., “Pre-and Post-Beamforming in MIMO Channels Applied to HIPERLAN/2 and OFDM”, IST Summit 2001, IST Mobile Communications Summit, Sep. 2001.
  • Ivrlac et al., “On Channel Capacity of Correlated MIMO Channels”, ITG Fokusprojekt: Mobilkommunikation “Systeme mit Intelligenten Antennen”, Ilmenau, 2001.
  • Jakes, “Microwave Mobile Communications”, Copyright 1974, pp. 313-320 and pp. 489-498.
  • Jungnickel et al., “A MIMO WLAN Based on Linear Channel Inversion”, IEE Seminar-MIMO Communication Systems from Concept To Implementation, Dec. 2001, pp. 20/1-20/6.
  • Jungnickel et al., “Performance of a MIMO System with Overlay Pilots”, IEEE GlobeCom 2001, pp. 594-598.
  • Li et al., “Adaptive Antenna Arrays for OFDM Systems With Cochannel Interference”, IEEE Transactions On Communications, vol. 47, No. 2, pp. 217-229, (Feb. 1999).
  • Love et al., “Equal Gain Transmission in Multiple-Input Multiple-Output Wireless Systems”, Nov. 2002, Proceedings of IEEE Globecom, pp. 1124-1128.
  • Lucent Technologies, “Lucent Technologies: Chips Posied to Bring ‘BLAST’ Multiple Input/Multiple Output Technology to Laptops, PDAs and Other Mobile Devices”, Oct. 16, 2002, lucent.com.
  • Morgan, “Interaction of Adaptive Antenna Arrays in an Arbitrary Environment”, The Bell System Technical Journal, Jan. 1965, pp. 23-47.
  • Narula et al., “Efficent Use of Side Information In Multiple-Antenna Data Transmission Over Fading Channels”, IEEE Journal On Selected Areas In Communications, vol. 16, No. 8, pp. 1423-1436 (Oct. 1998).
  • Onggosanusi et al., “Performance Analysis Of Closed-Loop Transmit Diversity In The Presence Of Feedback Delay”, IEEE Transactions On Communications, vol. 49, No. 9, pp. 1618-1630, (Sep. 2001).
  • Sanchez et al., “CSMA/CA Beam Forming Antennas in Multi-hop Packet Radio”; Proc. For Swedish Workshop on Wireless Ad-Hoc Networks, Mar. 5-6, 2001.
  • Stridh et al., “MIMO Channel Capacity on a Measured Indoor Radio Channel at 5.8 GHz”, Proc. of the Asilomar Conf. on Signals, Systems & Computers, vol. 1, Oct. 2000, pp. 733-737.
  • Vaidyanathan et al., “The Role in Lossless Systems in Modern Digital Signal Processing: A Tutorial”, IEEE Transactions on Education, vol. 32, Aug. 1989, pp. 181-197.
  • Wallace et al., “Experimental Characterization of the MIMO Wireless Cannel: Data Acquisition and Analysis”, Feb. 27, 2002, Department of Electrical and Computer Engineering, Brigham Young University.
  • Wolniansky et al., “V-BLAST: An Architecture for Realizing Very High Data Rates Over the Rich-Scattering Wireless Channel”, Proc. ISSSE-98, Pisa, Italy, Sep. 29, 1998.
  • Yang et al., “On Joint Transmitter and Receive Optimization for Multiple-Input-Multiple-Output (MIMO) Transmission Systems”, IEEE Transactions on Communications, vol. 42, No. 12, Dec. 1994.
  • Yeh, “An Analysis of Adaptive Retransmission Arrays in a Fading Environment”, The Bell System Technical Journal, Oct. 1970, pp. 1811-1825.
  • Chang et al., “Joint Transmitter Receiver Diversity For Efficient Space Division Multiaccess”, IEEE Transactions on Wireless Communications, vol. 1, No. 1, Jan. 2002.
  • Haardt et al., “Smart Antennas For UTRA TDD”, European Transactions On Telecommunications vol. 12, No. 5, Sep. 2001.
  • Lucent Technologies, “Lucent technologies: Chips poised to bring ‘BLAST’ Multiple Input/Multiple Output Technology to Laptops, PDAs and Other Mobile Devices”, Oct. 16, 2002, lucent.com.
  • Meyer-Ottens, et al. “Downlink Beamforming for W-CDMA Using Feedback and Interference Estimate”,Mar. 9, 2001.
  • Narula et al., “Efficient Use Of Side Information In Multiple-Antenna Data Transmission Over Fading Channels”, IEEE Journal On Selected Areas In Communications, vol. 16, No. 8, pp. 1423-1436, (Oct. 1998).
  • Perahia et al., “Adaptive Antenna Arrays and Equilization for Indoor Digital Radio,” IEEE International Conference on Communications, pp. 592-596 (Jun. 1996).
  • Siwiak, “Radiowave Propagation and Antennas for Personal Communications,” Artech House, Inc., pp. 31-37 (Apr. 1998).
  • Wallace et al., “Experimental Characterization of the MIMO Wireless Channel: Data Acquisition and Analysis”, Feb. 27, 2002, Department of Electrical and Computer Engineering, Brigham Young University.
Patent History
Patent number: RE45425
Type: Grant
Filed: Jan 31, 2013
Date of Patent: Mar 17, 2015
Assignee: IPR Licensing, Inc. (Wilmington, DE)
Inventors: Gary L. Sugar (San Francisco, CA), Chandra Vaidyanathan (Rockville, MD)
Primary Examiner: Blane J Jackson
Application Number: 13/755,945