Abstract: A receiving entity obtains received symbols for a data transmission having at least one data symbol stream sent with space-time transmit diversity (STTD). The receiving entity derives an overall channel response matrix in accordance with the STTD encoding scheme used for the data transmission, derives a spatial filter matrix based on the overall channel response matrix, and performs spatial matched filtering on a vector of received symbols for each 2-symbol interval to obtain a vector of detected symbols for the 2-symbol interval. The receiving entity may perform post-processing (e.g., conjugation) on the detected symbols if needed. Alternatively, the receiving entity derives a spatial filter matrix based on an effective channel response matrix, performs spatial matched filtering on the received symbols for each symbol period to obtain detected symbols for that symbol period, and combines multiple estimates obtained for each data symbol sent with STTD.

Abstract: A method for performing symbol timing estimation is disclosed herein. In one approach, the method includes defining a search space in a plurality of estimated magnitudes of channel taps; defining a search window in the search space; and locating a symbol timing estimate index in the search space corresponding to a maximum value of an energy of the plurality of estimated magnitudes of channel taps within the search window. A computer program product having code and a wireless communications apparatus for performing the method are also described herein.

Abstract: Techniques to parse data into multiple (M) streams with selectable data rates are described. The modulation scheme and code rate for each stream are determined based on the data rate selected for that stream. The modulation schemes and code rates for all M streams are used to determine a parse cycle and the number of puncture cycles for each stream in the parse cycle. A sequence of puncture cycles is formed for the M streams such that the puncture cycle(s) for each stream are distributed as evenly as possible across the sequence. An encoder encodes traffic data in accordance with a base code (e.g., a rate 1/2 binary convolutional code) and generates code bits. A parser then parses the code bits into the M streams based on the sequence of puncture cycles, one puncture cycle at a time and in the order indicated by the sequence.

Abstract: An access point in a multi-antenna system broadcasts data using spatial spreading to randomize an “effective” channel observed by each user terminal for each block of data symbols broadcast by the access point. At the access point, data is coded, interleaved, and modulated to obtain ND data symbol blocks to be broadcast in NM transmission spans, where ND?1 and NM>1. The ND data symbol blocks are partitioned into NM data symbol subblocks, one subblock for each transmission span. A steering matrix is selected (e.g., in a deterministic or pseudo-random manner from among a set of L steering matrices) for each subblock. Each data symbol subblock is spatially processed with the steering matrix selected for that subblock to obtain transmit symbols, which are further processed and broadcast via NT transmit antennas and in one transmission span to user terminals within a broadcast coverage area.

Abstract: An access point in a multi-antenna system broadcasts data using spatial spreading to randomize an “effective” channel observed by each user terminal for each block of data symbols broadcast by the access point. At the access point, data is coded, interleaved, and modulated to obtain ND data symbol blocks to be broadcast in NM transmission spans, where ND?1 and NM>1. The ND data symbol blocks are partitioned into NM data symbol subblocks, one subblock for each transmission span. A steering matrix is selected (e.g., in a deterministic or pseudo-random manner from among a set of L steering matrices) for each subblock. Each data symbol subblock is spatially processed with the steering matrix selected for that subblock to obtain transmit symbols, which are further processed and broadcast via NT transmit antennas and in one transmission span to user terminals within a broadcast coverage area.

Abstract: Techniques for decomposing matrices using Jacobi rotation are described. Multiple iterations of Jacobi rotation are performed on a first matrix of complex values with multiple Jacobi rotation matrices of complex values to zero out the off-diagonal elements in the first matrix. For each iteration, a submatrix may be formed based on the first matrix and decomposed to obtain eigenvectors for the submatrix, and a Jacobi rotation matrix may be formed with the eigenvectors and used to update the first matrix. A second matrix of complex values, which contains orthogonal vectors, is derived based on the Jacobi rotation matrices. For eigenvalue decomposition, a third matrix of eigenvalues may be derived based on the Jacobi rotation matrices. For singular value decomposition, a fourth matrix with left singular vectors and a matrix of singular values may be derived based on the Jacobi rotation matrices.

Abstract: Techniques for performing sphere detection to recover data symbols sent in a MIMO transmission are described. In an aspect, sphere detection is performed for data symbols generated with at least two modulation schemes. In another aspect, sphere detection is performed for the data symbols in an order determined based on at least one attribute of the data symbols, which may be error probabilities, modulation schemes, and/or link margins for the data symbols. In yet another aspect, rates for multiple data streams detected with sphere detection are selected based on channel state information. Signal qualities of the data streams may be estimated based on the channel state information, e.g., (1) an upper triangular matrix used for sphere detection and/or (2) an assumption that interference from data streams already detected is canceled. The rates for the data streams may be selected based on the estimated signal qualities.

Abstract: Frequency-independent eigensteering in MISO and MIMO systems are described. For principal mode and multi-mode eigensteering, a correlation matrix is computed for a MIMO channel based on channel response matrices and decomposed to obtain NS frequency-independent steering vectors for NS spatial channels of the MIMO channel. ND data symbol streams are transmitted on ND best spatial channels using ND steering vectors, where ND=1 for principal mode eigensteering and ND>1 for multi-mode eigensteering. For main path eigensteering, a data symbol stream is transmitted on the best spatial channel for the main propagation path (e.g., with the highest energy) of the MIMO channel. For receiver eigensteering, a data symbol stream is steered toward a receive antenna based on a steering vector obtained for that receive antenna. For all eigensteering schemes, a matched filter is derived for each receive antenna based on the steering vector(s) and channel response vectors for the receive antenna.

Abstract: Techniques for transmitting data using a combination of transmit diversity schemes are described. These transmit diversity schemes include spatial spreading, continuous beamforming, cyclic delay diversity, space-time transmit diversity (STTD), space-frequency transmit diversity (SFTD), and orthogonal transmit diversity (OTD). A transmitting entity processes one or more (ND) data symbol streams based on a transmit diversity scheme (e.g., STTD, SFTD, or OTD) to generate multiple (NC) coded symbol streams. Each data symbol stream may be sent as a single coded symbol stream or as multiple (e.g., two) coded symbol streams using STTD, SFTD, or OTD. The transmitting entity may perform spatial spreading on the NC coded symbol streams with different matrices to generate multiple (NT) transmit symbol streams for transmission from NT antennas. Additionally or alternatively, the transmitting entity may perform continuous beamforming on the NT transmit symbol streams in either the time domain or the frequency domain.

Abstract: Techniques for selecting rates for data transmission on eigenmodes of a MIMO channel are described. An access point transmits an unsteered MIMO pilot via the downlink. A user terminal estimates the downlink channel quality based on the downlink unsteered MIMO pilot and transmits an unsteered MIMO pilot and feedback information via the uplink. The feedback information is indicative of the downlink channel quality. The access point estimates the uplink channel quality and obtains a channel response matrix based on the uplink unsteered MIMO pilot, decomposes the channel response matrix to obtain eigenvectors and channel gains for the eigenmodes of the downlink, and selects rates for the eigenmodes based on the estimated uplink channel quality, the channel gains for the eigenmodes, and the feedback information. The access point processes data based on the selected rates and transmits steered data and a steered MIMO pilot on the eigenmodes with the eigenvectors.