Abstract:
PROBLEM TO BE SOLVED: To provide continuous beamforming for a MIMO-OFDM system.SOLUTION: A transmitting entity 210 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 are 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 234. A receiving entity 250 performs complementary processing to recover the data symbols sent by the transmitting entity. The receiving entity derives a spatial filter matrix for each subband on the basis of a MIMO channel response for that subband and performs receiver spatial processing for the subband with the spatial filter matrix.
Abstract:
PROBLEM TO BE SOLVED: To provide a receiver for wireless communication network with an extended range. SOLUTION: A technique for detecting and demodulating a signal/transmission is described. The signal detection is performed in a plurality of stages using different types of signal processing, such as, for example, using time-domain correlation in a first stage, frequency-domain processing in a second stage, and time-domain processing in a third stage. In the first stage, products of symbols are generated for at least two different delays, correlation processing between the products of respective delays and known values is performed, and correlation results for all delays are combined to declare the presence of a signal. In the demodulation, the timing of input samples is adjusted to obtain timing-adjusted samples. A frequency offset is estimated and removed from the timing-adjusted samples to obtain frequency-corrected sample, which are processed through channel estimate to obtain detected symbols. COPYRIGHT: (C)2011,JPO&INPIT
Abstract:
PROBLEM TO BE SOLVED: To efficiently derive a spatial filter matrix. SOLUTION: In a first scheme, a Hermitian matrix is iteratively derived based on a channel response matrix, and a matrix inversion is indirectly calculated by deriving the Hermitian matrix iteratively. The spatial filter matrix is derived based on the Hermitian matrix and the channel response matrix. In a second scheme, multiple rotations are performed to iteratively obtain first and second matrices for a pseudo-inverse matrix of the channel response matrix. The spatial filter matrix is derived based on the first and second matrices. In a third scheme, a matrix is formed based on the channel response matrix and decomposed to obtain a unitary matrix and a diagonal matrix. The spatial filter matrix is derived based on the unitary matrix, the diagonal matrix, and the channel response matrix. COPYRIGHT: (C)2011,JPO&INPIT
Abstract:
PROBLEM TO BE SOLVED: To provide techniques for selecting a proper set of user terminals for simultaneous transmission, and transmitting and receiving data between the selected user terminals. SOLUTION: An uplink channel response matrix is obtained for each terminal and decomposed to obtain a steering vector for use 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 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. COPYRIGHT: (C)2010,JPO&INPIT
Abstract:
PROBLEM TO BE SOLVED: To achieve transmit diversity for a legacy single-antenna receiving device. SOLUTION: A multi-antenna transmitting entity transmits data to a single- or multi-antenna receiving entity using (1) a steered mode to direct the data transmission toward the receiving entity or (2) a pseudo-random transmit steering (PRTS) mode to randomize the effective channels observed by the data transmission across the subbands. The receiving entity does not need to have knowledge of the pseudo-random steering vectors or perform any special processing. For spatial spreading, the transmitting entity uses different pseudo-random steering vectors across the subbands and different steering vectors across the packet for each subband. COPYRIGHT: (C)2010,JPO&INPIT
Abstract:
PROBLEM TO BE SOLVED: To provide a device for deriving and using noise estimate for data reception in a wireless communication system.SOLUTION: A noise estimate may be derived for each packet received in a data transmission. Data detection is then performed for each packet using the noise estimate for the packet. For the noise estimation, a first sample sequence and a second sample sequence may be obtained from each receiver used for data reception. A phase offset between the first and second sample sequences is determined and applied to the first sample sequence for each receiver to obtain a third sample sequence for the receiver. A noise estimate may then be obtained based on the differences in electric power between the second and third sample sequences for the at least one receiver.
Abstract:
PROBLEM TO BE SOLVED: To provide frequency-independent eigensteering in MISO and MIMO systems.SOLUTION: 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. For main path eigensteering, a data symbol stream is transmitted on the best spatial channel for the main propagation path 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:
PROBLEM TO BE SOLVED: To provide techniques for deriving and using noise estimation for data reception in a wireless communication system.SOLUTION: A noise estimation may be derived for each packet received in data transmission. Data detection may then be performed for each packet using the noise estimation for that packet. For the noise estimation, a first sample sequence and a second sample sequence may be obtained from each receiver used for data reception. A phase offset between the first and second sample sequences may be determined and applied to the first sample sequence for each receiver to obtain a third sample sequence for that receiver. A noise estimation may then be derived based on the power of the differences between the second and third sample sequences for at least one receiver.
Abstract:
PROBLEM TO BE SOLVED: To provide a novel and improved method and apparatus for processing data for transmission in a wireless communication system using selective channel inversion. SOLUTION: The method 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 above a particular threshold are selected, "bad" channels are not used, and the total available transmit power is distributed across only "good" channels. COPYRIGHT: (C)2011,JPO&INPIT
Abstract:
PROBLEM TO BE SOLVED: To achieve transmission diversity on a legacy single-antenna receiving device. SOLUTION: In order to obtain transmission diversity, a transmission entity uses different pseudo-random steering vectors across subbands, and uses the same steering vector across packets for each subband. A receiving entity does not need to know the pseudo-random steering vectors and further does not need to perform any space processing. For space spreading, the transmission entity uses different pseudo-random steering vectors across the subbands and uses different steering vectors across the packets for each subband. Only the transmission and the receiving entities know the steering vectors used for data transmission. COPYRIGHT: (C)2010,JPO&INPIT