Abstract: Methods and systems are described for jointly processing multiple sectors in a wireless communication network. In one aspect, a first antenna serving a first sector is associated with a second antenna serving a second sector for joint processing. First and second antenna data is received. A plurality of wireless users associated with at least one of the first or second antenna data to model for channel estimation is determined, including an interfering wireless user connected via a third antenna serving a third sector not currently being jointly processed with the first or second antenna data. Channel estimates are determined for the plurality of wireless users. The first and second antenna data is jointly processed. Interference from the wireless user connected via a third antenna is suppressed based on a determined corresponding channel estimate for the wireless user and other received information for the wireless user.

Abstract: Methods and systems for performing compressed time domain joint channel estimation in a multi-user MIMO wireless network include receiving data corresponding to transmission of training signals from a plurality of users to a base station over a MIMO wireless network, determining a limited data set by limiting the received data in a time domain according to an estimated maximum delay spread, forming a well-conditioned low rank training matrix by identifying a channel model, estimating an active tap from the formed well-conditioned low rank training matrix, and subtracting a contribution of the selected active tap from the limited data set.

Abstract: Methods and systems for performing compressed time domain joint channel estimation in a multi-user MIMO wireless network include receiving data corresponding to transmission of training signals from a plurality of users to a base station over a MIMO wireless network, determining a limited data set by limiting the received data in a time domain according to an estimated maximum delay spread, forming a well-conditioned low rank training matrix by identifying a channel model, estimating an active tap from the formed well-conditioned low rank training matrix, and subtracting a contribution of the selected active tap from the limited data set.

Abstract: An improved receiver design implements a method for modeling users in SIC turbo loop multiuser detection architectures that reduces the number of implementation cycles, and thereby reduces the computational overhead associated with computing the inverse of the received signal covariance matrix, by efficiently reusing components of a QR decomposition. By reusing some of the computational results from the previous turbo loop's equalizer calculation, the disclosed receiver significantly reduces the computational burden of updating the linear equalizer on each turbo loop. Depending on the embodiment, this reduction can be accomplished in at least two different ways, depending on the dimensionality and other aspects of the implementation.

Abstract: An improved receiver design implements a practical method for modeling users in SIC turbo loop multiuser detection architectures, wherein in each loop unsubtracted estimation errors from previous loops are used to appropriately scale the error covariance matrix for each user, thereby accurately representing the remaining residual interference in the data stream for each desired user. The effect of estimation errors in previous interference cancellation operations is thereby minimized, and symbol estimations in successive turbo loops are improved, for example during multiuser MMSE, multiuser MMSE with interference rejection combining (MMSE-IRC), sample matrix inversion (SMI), or any of their adaptive variants (least mean-square, recursive least square, Kalman filter etc.). The estimated residual symbol energy can be computed per symbol, and then applied to entire data streams, to groups of symbols, or to each symbol separately.

Abstract: Methods and systems for performing compressed time domain joint channel estimation in a multi-user MIMO wireless network include receiving training signals from a plurality of users, estimating a maximum delay spread for the received data according to a coherence bandwidth of the received data, limiting the received data in the time domain to the estimated maximum delay spread, selecting and estimating an active tap from the limited data set, and subtracting a contribution of the selected active tap from the reduced data set. These steps can be repeated until the residual signal falls below a specified minimum. The network can be a C-RAN network. The training data can be SRS or DMRS data. Limiting the received data ensures that only a few significant taps are analyzed, so that the system is not under determined and can be analyzed for accurate channel estimation using any of several existing algorithms.

Abstract: Methods and systems for performing compressed time domain joint channel estimation in a multi-user MIMO wireless network include receiving training signals from a plurality of users, estimating a maximum delay spread for the received data according to a coherence bandwidth of the received data, limiting the received data in the time domain to the estimated maximum delay spread, selecting and estimating an active tap from the limited data set, and subtracting a contribution of the selected active tap from the reduced data set. These steps can be repeated until the residual signal falls below a specified minimum. The network can be a C-RAN network. The training data can be SRS or DMRS data. Limiting the received data ensures that only a few significant taps are analyzed, so that the system is not under determined and can be analyzed for accurate channel estimation using any of several existing algorithms.

Abstract: An improved receiver design implements a practical method for modeling users in SIC turbo loop multiuser detection architectures, wherein in each loop unsubtracted estimation errors from previous loops are used to appropriately scale the error covariance matrix for each user, thereby accurately representing the remaining residual interference in the data stream for each desired user. The effect of estimation errors in previous interference cancellation operations is thereby minimized, and symbol estimations in successive turbo loops are improved, for example during multiuser MMSE, multiuser MMSE with interference rejection combining (MMSE-IRC), sample matrix inversion (SMI), or any of their adaptive variants (least mean-square, recursive least square, Kalman filter etc.). The estimated residual symbol energy can be computed per symbol, and then applied to entire data streams, to groups of symbols, or to each symbol separately.

Abstract: Methods and systems are described for jointly processing multiple sectors in a wireless communication network. In one aspect, a first antenna serving a first sector is associated with a second antenna serving a second sector for joint processing. First and second antenna data is received. A plurality of wireless users associated with at least one of the first or second antenna data to model for channel estimation is determined, including an interfering wireless user connected via a third antenna serving a third sector not currently being jointly processed with the first or second antenna data. Channel estimates are determined for the plurality of wireless users. The first and second antenna data is jointly processed. Interference from the wireless user connected via a third antenna is suppressed based on a determined corresponding channel estimate for the wireless user and other received information for the wireless user.

Abstract: Methods and systems for performing compressed time domain joint channel estimation in a multi-user MIMO wireless network include receiving training signals from a plurality of users, estimating a maximum delay spread for the received data according to a coherence bandwidth of the received data, limiting the received data in the time domain to the estimated maximum delay spread, selecting and estimating an active tap from the limited data set, and subtracting a contribution of the selected active tap from the reduced data set. These steps can be repeated until the residual signal falls below a specified minimum. The network can be a C-RAN network. The training data can be SRS or DMRS data. Limiting the received data ensures that only a few significant taps are analyzed, so that the system is not under determined and can be analyzed for accurate channel estimation using any of several existing algorithms.

Abstract: An improved receiver design implements a method for modeling users in SIC turbo loop multiuser detection architectures that reduces the number of implementation cycles, and thereby reduces the computational overhead associated with computing the inverse of the received signal covariance matrix, by efficiently reusing components of a QR decomposition. By reusing some of the computational results from the previous turbo loop's equalizer calculation, the disclosed receiver significantly reduces the computational burden of updating the linear equalizer on each turbo loop. Depending on the embodiment, this reduction can be accomplished in at least two different ways, depending on the dimensionality and other aspects of the implementation.

Abstract: Methods and systems for obtaining improved joint channel estimates for a multi-user, frequency-multiplexed data transmission such as SC-FDMA or OFDM begins by estimating separate contributions of users (and/or other signal sources) to the received signal based on joint frequency domain channel estimates. A reduced data set is obtained by subtracting contributions of one or more users from the received data, leaving only the estimated contributions of the remaining users, with noise and residual estimation error signal. Time domain joint channel estimation is then performed on the reduced data set, which is feasible because the number of users has been reduced. In exemplary embodiments, the reduced data set includes only one estimated user contribution. This process is repeated to obtain channel estimates for all of the users. The method can be repeated by using the channel estimates to re-estimate the user contributions and calculate revised channel estimates.

Abstract: An improved receiver design implements a practical method for modeling users in SIC turbo loop multiuser detection architectures, wherein in each loop unsubtracted estimation errors from previous loops are used to appropriately scale the error covariance matrix for each user, thereby accurately representing the remaining residual interference in the data stream for each desired user. The effect of estimation errors in previous interference cancellation operations is thereby minimized, and symbol estimations in successive turbo loops are improved, for example during multiuser MMSE, multiuser MMSE with interference rejection combining (MMSE-IRC), sample matrix inversion (SMI), or any of their adaptive variants (least mean-square, recursive least square, Kalman filter etc.). The estimated residual symbol energy can be computed per symbol, and then applied to entire data streams, to groups of symbols, or to each symbol separately.

Abstract: An improved receiver design implements a method for modeling users in SIC turbo loop multiuser detection architectures that reduces the number of implementation cycles, and thereby reduces the computational overhead associated with computing the inverse of the received signal covariance matrix, by efficiently reusing components of a QR decomposition. By reusing some of the computational results from the previous turbo loop's equalizer calculation, the disclosed receiver significantly reduces the computational burden of updating the linear equalizer on each turbo loop. Depending on the embodiment, this reduction can be accomplished in at least two different ways, depending on the dimensionality and other aspects of the implementation.

Abstract: Methods and systems are described for jointly processing multiple sectors in a wireless communication network. In one aspect, a first antenna serving a first sector is associated with a second antenna serving a second sector for joint processing. First and second antenna data is received. A plurality of wireless users associated with at least one of the first or second antenna data to model for channel estimation is determined, including an interfering wireless user connected via a third antenna serving a third sector not currently being jointly processed with the first or second antenna data. Channel estimates are determined for the plurality of wireless users. The first and second antenna data is jointly processed. Interference from the wireless user connected via a third antenna is suppressed based on a determined corresponding channel estimate for the wireless user and other received information for the wireless user.

Abstract: Methods and systems are described for communication channel prediction from received multipath communications in a wireless communications system. In one aspect, a baseband impairment compensation of at least one of sample frequency offset, carrier frequency offset, and time offset between a wireless transmitter and a wireless receiver is estimated. A plurality of complex value channel tap estimates is received for each of a plurality of channel taps. A plurality of complex value channel tap predictions is determined for a future multipath communication based on the prior received corresponding complex value channel tap estimates and the baseband impairment compensation.

Abstract: An improved receiver design implements a practical method for modeling users in SIC turbo loop multiuser detection architectures, wherein in each loop unsubtracted estimation errors from previous loops are used to appropriately scale the error covariance matrix for each user, thereby accurately representing the remaining residual interference in the data stream for each desired user. The effect of estimation errors in previous interference cancellation operations is thereby minimized, and symbol estimations in successive turbo loops are improved, for example during multiuser MMSE, multiuser MMSE with interference rejection combining (MMSE-IRC), sample matrix inversion (SMI), or any of their adaptive variants (least mean-square, recursive least square, Kalman filter etc.). The estimated residual symbol energy can be computed per symbol, and then applied to entire data streams, to groups of symbols, or to each symbol separately.

Abstract: Methods and systems for processing communications based on wireless communications of adjacent base stations are disclosed. According to an aspect, a method includes monitoring, by a separate interference monitoring receiver communicatively coupled to a first base station, wireless communications transmitted by a second base station to communicate with one or more mobile devices. The method also includes determining, based on the monitored wireless communications, a wireless communication scheme for processing communications between the first base station and one or more other mobile devices. Further, the method includes processing communications between the first base station and the one or more other mobile devices based on the wireless communication scheme.

Abstract: An improved receiver design implements a method for modeling users in SIC turbo loop multiuser detection architectures that reduces the number of implementation cycles, and thereby reduces the computational overhead associated with computing the inverse of the received signal covariance matrix, by efficiently reusing components of a QR decomposition. By reusing some of the computational results from the previous turbo loop's equalizer calculation, the disclosed receiver significantly reduces the computational burden of updating the linear equalizer on each turbo loop. Depending on the embodiment, this reduction can be accomplished in at least two different ways, depending on the dimensionality and other aspects of the implementation.

Abstract: An improved receiver design implements a practical method for modeling users in SIC turbo loop multiuser detection architectures, wherein in each loop unsubtracted estimation errors from previous loops are used to appropriately scale the error covariance matrix for each user, thereby accurately representing the remaining residual interference in the data stream for each desired user. The effect of estimation errors in previous interference cancellation operations is thereby minimized, and symbol estimations in successive turbo loops are improved, for example during multiuser MMSE, multiuser MMSE with interference rejection combining (MMSE-IRC), sample matrix inversion (SMI), or any of their adaptive variants (least mean-square, recursive least square, Kalman filter etc.). The estimated residual symbol energy can be computed per symbol, and then applied to entire data streams, to groups of symbols, or to each symbol separately.