Abstract: For eigenmode transmission with minimum mean square error (MMSE) receiver spatial processing, a transmitter performs spatial processing on NS data symbol streams with steering vectors to transmit the streams on NS spatial channels of a MIMO channel. The steering vectors are estimates of transmitter steering vectors required to orthogonalize the spatial channels. A receiver derives a spatial filter based on an MMSE criterion and with an estimate of the MIMO channel response and the steering vectors. The receiver (1) obtains NR received symbol streams from NR receive antennas, (2) performs spatial processing on the received symbol streams with the spatial filter to obtain NS filtered symbol streams, (3) performs signal scaling on the filtered symbol streams with a scaling matrix to obtain NS recovered symbol streams, and (4) processes the NS recovered symbol streams to obtain NS decoded data streams for the NS data streams sent by the transmitter.

Abstract: For transmit diversity in a multi-antenna OFDM system, a transmitter encodes, interleaves, and symbol maps traffic data to obtain data symbols. The transmitter processes each pair of data symbols to obtain two pairs of transmit symbols for transmission from a pair of antennas either (1) in two OFDM symbol periods for space-time transmit diversity or (2) on two subbands for space-frequency transmit diversity. NT·(NT?1)/2 different antenna pairs are used for data transmission, with different antenna pairs being used for adjacent subbands, where NT is the number of antennas. The system may support multiple OFDM symbol sizes. The same coding, interleaving, and modulation schemes are used for different OFDM symbol sizes to simplify the transmitter and receiver processing. The transmitter performs OFDM modulation on the transmit symbol stream for each antenna in accordance with the selected OFDM symbol size. The receiver performs the complementary processing.

Abstract: For data transmission with spatial spreading, a transmitting entity (1) encodes and modulates each data packet to obtain a corresponding data symbol block, (2) multiplexes data symbol blocks onto NS data symbol streams for transmission on NS transmission channels of a MIMO channel, (3) spatially spreads the NS data symbol streams with steering matrices, and (4) spatially processes NS spread symbol streams for full-CSI transmission on NS eigenmodes or partial-CSI transmission on NS spatial channels of the MIMO channel. A receiving entity (1) obtains NR received symbol streams via NR receive antennas, (2) performs receiver spatial processing for full-CSI or partial-CSI transmission to obtain NS detected symbol streams, (3) spatially despreads the NS detected symbol streams with the same steering matrices used by the transmitting entity to obtain NS recovered symbol streams, and (4) demodulates and decodes each recovered symbol block to obtain a corresponding decoded data packet.

Abstract: In one aspect of a multiple-access OFDM-CDMA system, the data spreading is performed in the frequency domain by spreading each data stream with a respective spreading code selected from a set of available spreading codes. To support multiple access, system resources may be allocated and de-allocated to users (e.g., spreading codes may be assigned to users as needed, and transmit power may be allocated to users). Variable rate data for each user may be supported via a combination of spreading adjustment and transmit power scaling. Interference control techniques are also provided to improve system performance via power control of the downlink and/or uplink transmissions to achieve the desired level of performance while minimizing interference. A pilot may be transmitted by each transmitter unit to assist the receiver units perform acquisition, timing synchronization, carrier recovery, handoff, channel estimation, coherent data demodulation, and so on.

Abstract: For eigenvalue decomposition, a first set of at least one variable is derived based on a first matrix being decomposed and using Coordinate Rotational Digital Computer (CORDIC) computation. A second set of at least one variable is derived based on the first matrix and using a look-up table. A second matrix of eigenvectors of the first matrix is then derived based on the first and second variable sets. To derive the first variable set, CORDIC computation is performed on an element of the first matrix to determine the magnitude and phase of this element, and CORDIC computation is performed on the phase to determine the sine and cosine of this element. To derive the second variable set, intermediate quantities are derived based on the first matrix and used to access the look-up table.

Abstract: For eigenmode transmission with minimum mean square error (MMSE) receiver spatial processing, a transmitter performs spatial processing on NS data symbol streams with steering vectors to transmit the streams on NS spatial channels of a MIMO channel. The steering vectors are estimates of transmitter steering vectors required to orthogonalize the spatial channels. A receiver derives a spatial filter based on an MMSE criterion and with an estimate of the MIMO channel response and the steering vectors. The receiver (1) obtains NR received symbol streams from NR receive antennas, (2) performs spatial processing on the received symbol streams with the spatial filter to obtain NS filtered symbol streams, (3) performs signal scaling on the filtered symbol streams with a scaling matrix to obtain NS recovered symbol streams, and (4) processes the NS recovered symbol streams to obtain NS decoded data streams for the NS data streams sent by the transmitter.

Abstract: A MIMO system supports multiple spatial multiplexing modes for improved performance and greater flexibility. These modes may include (1) a single-user steered mode that transmits multiple data streams on orthogonal spatial channels to a single receiver, (2) a single-user non-steered mode that transmits multiple data streams from multiple antennas to a single receiver without spatial processing at a transmitter, (3) a multi-user steered mode that transmits multiple data streams simultaneously to multiple receivers with spatial processing at a transmitter, and (4) a multi-user non-steered mode that transmits multiple data streams from multiple antennas (co-located or non co-located) without spatial processing at the transmitter(s) to receiver(s) having multiple antennas. For each set of user terminal(s) selected for data transmission on the downlink and/or uplink, a spatial multiplexing mode is selected for the user terminal set from among the multiple spatial multiplexing modes supported by the system.

Abstract: For eigenvalue decomposition, a first set of at least one variable is derived based on a first matrix being decomposed and using Coordinate Rotational Digital Computer (CORDIC) computation. A second set of at least one variable is derived based on the first matrix and using a look-up table. A second matrix of eigenvectors of the first matrix is then derived based on the first and second variable sets. To derive the first variable set, CORDIC computation is performed on an element of the first matrix to determine the magnitude and phase of this element, and CORDIC computation is performed on the phase to determine the sine and cosine of this element. To derive the second variable set, intermediate quantities are derived based on the first matrix and used to access the look-up table.

Abstract: Techniques to process data for transmission over a set of transmission channels selected from among all available transmission channels. In an aspect, the data processing includes coding data based on a common coding and modulation scheme to provide modulation symbols and pre-weighting the modulation symbols for each selected channel based on the channel's characteristics. The pre-weighting may be achieved by “inverting” the selected channels so that the received SNRs are approximately similar for all selected channels. With selective channel inversion, only channels having SNRs at or above a particular threshold are selected, “bad” channels are not used, and the total available transmit power is distributed across only “good” channels. Improved performance is achieved due to the combined benefits of using only the NS best channels and matching the received SNR of each selected channel to the SNR required by the selected coding and modulation scheme.

Abstract: Techniques to process data for transmission over a set of transmission channels selected from among all available transmission channels. In an aspect, the data processing includes coding data based on a common coding and modulation scheme to provide modulation symbols and pre-weighting the modulation symbols for each selected channel based on the channel's characteristics. The pre-weighting may be achieved by “inverting” the selected channels so that the received SNRs are approximately similar for all selected channels. With selective channel inversion, only channels having SNRs at or above a particular threshold are selected, “bad” channels are not used, and the total available transmit power is distributed across only “good” channels. Improved performance is achieved due to the combined benefits of using only the Ns best channels and matching the received SNR of each selected channel to the SNR required by the selected coding and modulation scheme.

Abstract: A “unified” MIMO system that supports multiple operating modes for efficient data transmission is described. Each operating mode is associated with different spatial processing at a transmitting entity. For example, four operating modes may be defined for (1) full-CSI or partial-CSI transmission and (2) with or without steering transmit diversity (STD). An appropriate operating mode may be selected for use based on various factors (e.g., availability of a good channel estimate). With steering transmit diversity, data is spatially spread and transmitted on multiple spatial channels, and a single rate may then be used for all spatial channels used for data transmission. A receiving entity may utilize a minimum mean square error (MMSE) technique for all operating modes. The receiving entity may derive a spatial filter matrix and perform receiver spatial processing in the same manner for all operating modes, albeit with different effective channel response matrices.

Abstract: Techniques to process data for transmission over a set of transmission channels selected from among all available transmission channels. In an aspect, the data processing includes coding data based on a common coding and modulation scheme to provide modulation symbols and pre-weighting the modulation symbols for each selected channel based on the channel's characteristics. The pre-weighting may be achieved by “inverting” the selected channels so that the received SNRs are approximately similar for all selected channels. With selective channel inversion, only channels having SNRs at or above a particular threshold are selected, “bad” channels are not used, and the total available transmit power is distributed across only “good” channels. Improved performance is achieved due to the combined benefits of using only the NS best channels and matching the received SNR of each selected channel to the SNR required by the selected coding and modulation scheme.

Abstract: Channel estimation and spatial processing for a TDD MIMO system. Calibration may be performed to account for differences in the responses of transmit/receive chains at the access point and user terminal. During normal operation, a MIMO pilot is transmitted on a first link and used to derive an estimate of the first link channel response, which is decomposed to obtain a diagonal matrix of singular values and a first unitary matrix containing both left eigenvectors of the first link and right eigenvectors of a second link. A steered reference is transmitted on the second link using the eigenvectors in the first unitary matrix, and is processed to obtain the diagonal matrix and a second unitary matrix containing both left eigenvectors of the second link and right eigenvectors of the first link. Each unitary matrix may be used to perform spatial processing for data transmission/reception via both links.

Abstract: Techniques for transmitting data from a transmitter unit to a receiver unit in a multiple-input multiple-output (MIMO) communication system. In one method, at the receiver unit, a number of signals are received via a number of receive antennas, with the received signal from each receive antenna comprising a combination of one or more signals transmitted from the transmitter unit. The received signals are processed to derive channel state information (CSI) indicative of characteristics of a number of transmission channels used for data transmission. The CSI is transmitted back to the transmitter unit. At the transmitter unit, the CSI from the receiver unit is received and data for transmission to the receiver unit is processed based on the received CSI.

Abstract: Techniques to achieve better utilization of the available resources and robust performance for the downlink and uplink in a multiple-access MIMO system. Techniques are provided to adaptively process data prior to transmission, based on channel state information, to more closely match the data transmission to the capacity of the channel. Various receiver processing techniques are provided to process a data transmission received via multiple antennas at a receiver unit. Adaptive reuse schemes and power back-off are also provided to operate the cells in the system in a manner to further increase the spectral efficiency of the system (e.g., reduce interference, improve coverage, and attain high throughput). Techniques are provided to efficiently schedule data transmission on the downlink and uplink. The scheduling schemes may be designed to optimize transmissions (e.g., maximize throughput) for single or multiple terminals in a manner to meet various constraints and requirements.

Abstract: A transmitting entity performs spatial processing on data symbols for each subband with an eigenmode matrix, a steering matrix, or an identity matrix to obtain spatially processed symbols for the subband. The data symbols may be sent on orthogonal spatial channels with the eigenmode matrix, on different spatial channels with the steering matrix, or from different transmit antennas with the identity matrix. The transmitting entity further performs beamforming on the spatially processed symbols, in the frequency domain or time domain, prior to transmission from the multiple transmit antennas. A receiving entity performs the complementary processing to recover the data symbols sent by the transmitting entity. The receiving entity may derive a spatial filter matrix for each subband based on a MIMO channel response matrix for that subband and perform receiver spatial processing for the subband with the spatial filter matrix.

Abstract: Techniques for transmitting data from a transmitter unit to a receiver unit in a multiple-input multiple-output (MIMO) communication system. In one method, at the receiver unit, a number of signals are received via a number of receive antennas, with the received signal from each receive antenna comprising a combination of one or more signals transmitted from the transmitter unit. The received signals are processed to derive channel state information (CSI) indicative of characteristics of a number of transmission channels used for data transmission. The CSI is transmitted back to the transmitter unit. At the transmitter unit, the CSI from the receiver unit is received and data for transmission to the receiver unit is processed based on the received CSI.

Abstract: An uplink channel response matrix is obtained for each terminal and decomposed to obtain a steering vector used by the terminal to transmit on the uplink. An “effective” uplink channel response vector is formed for each terminal based on its steering vector and its channel response matrix. Multiple sets of terminals are evaluated based on their effective channel response vectors to determine the best set (e.g., with highest overall throughput) for uplink transmission. Each selected terminal performs spatial processing on its data symbol stream with its steering vector and transmits its spatially processed data symbol stream to an access point. The multiple selected terminals simultaneously transmit their data symbol streams via their respective MIMO channels to the access point. The access point performs receiver spatial processing on its received symbol streams in accordance with a receiver spatial processing technique to recover the data symbol streams transmitted by the selected terminals.

Abstract: Techniques for processing a data transmission at the transmitter and receiver. In an aspect, a time-domain implementation is provided which uses frequency-domain singular value decomposition and “water-pouring” results to derive time-domain pulse-shaping and beam-steering solutions at the transmitter and receiver. The singular value decomposition is performed at the transmitter to determine eigen-modes (i.e., spatial subchannels) of the MIMO channel and to derive a first set of steering vectors used to “precondition” modulation symbols. The singular value decomposition is also performed at the receiver to derive a second set of steering vectors used to precondition the received signals such that orthogonal symbol streams are recovered at the receiver, which can simplify the receiver processing. Water-pouring analysis is used to more optimally allocate the total available transmit power to the eigen-modes, which then determines the data rate and the coding and modulation scheme to be used for each eigen-mode.

Abstract: A multiple-access MIMO WLAN system that employs MIMO, OFDM, and TDD. The system (1) uses a channel structure with a number of configurable transport channels, (2) supports multiple rates and transmission modes, which are configurable based on channel conditions and user terminal capabilities, (3) employs a pilot structure with several types of pilot (e.g., beacon, MIMO, steered reference, and carrier pilots) for different functions, (4) implements rate, timing, and power control loops for proper system operation, and (5) employs random access for system access by the user terminals, fast acknowledgment, and quick resource assignments. Calibration may be performed to account for differences in the frequency responses of transmit/receive chains at the access point and user terminals. The spatial processing may then be simplified by taking advantage of the reciprocal nature of the downlink and uplink and the calibration.