Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a network node, one or more control channel symbols in a subframe. The UE may activate a sleep mode for the subframe irrespective of a control channel decoding result associated with the one or more control channel symbols, wherein the control channel decoding result is associated with a presence or an absence of a downlink shared channel grant. Numerous other aspects are described.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a receiving device may receive a wireless signal represented as a receive matrix. The wireless signal carries one or more information symbols modified through a wireless channel that is represented as a channel matrix. The receiving device may perform QR decomposition on the channel matrix to generate an upper triangular channel matrix. The receiving device may determine a selected demapping technique using the upper triangular channel matrix. The receiving device may perform the selected demapping technique on the receive matrix and the channel matrix. Numerous other aspects are described.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a receiving device may receive a wireless signal represented as a receive matrix. The wireless signal carries one or more information symbols modified through a wireless channel that is represented as a channel matrix. The receiving device may perform QR decomposition on the channel matrix to generate an upper triangular channel matrix. The receiving device may determine a selected demapping technique using the upper triangular channel matrix. The receiving device may perform the selected demapping technique on the receive matrix and the channel matrix. Numerous other aspects are described.

Abstract: The present disclosure describes apparatuses and methods for dynamic interference cancellation in wireless receivers. In some aspects, a signal vector transmitted through a wireless environment is received via multiple antennas of a receiver, the signal vector affected by interfering signals in the wireless environment. The receiver determines an interference channel matrix for the signal vector based on the interference received with the signal vector and selects, from the interference channel matrix, columns of the interference channel matrix to form a noise-cancelling equalization matrix. The receiver then equalizes the signal vector with the noise-cancelling equalization matrix to remove a portion of interference from the signal vector to provide noise-cancelled equalized values of the signal vector for decoding. By so doing, the receiver may reduce effects of interference of the wireless environment (e.g.

Abstract: Embodiments described herein provide a method for time delay estimation in a wireless communication system. A signal received, from a transmitter, is delayed due to hardware components in the receiver. A time domain representation of a computed complex channel impulse response (CIR) is generated. A first set of peaks of a time domain representation of the complex CIR is determined and a first peak, having a lowest time delay of the first set of peaks relative to the arrival time of the signal at the receiver, is identified. Following the interpolation of a region corresponding to the first peak, a second set of peaks is determined, and a more accurate estimation of the delay experienced by the signal through the receiver is determined.

Abstract: Systems and methods for detecting data in a received multiple-input-multiple-output signal are provided. N signals are received from N respective antennas, where the received signals are associated with (i) M sets of data values, (ii) a set of symbols, and (iii) a set of carrier frequencies. The N signals are formed into a received signal vector y, and one or more transformations are performed on the received signal vector y to obtain a transformed vector. A plurality of samples are formed from the transformed vector. For samples of the plurality of samples, a data detection technique of a plurality of data detection techniques is selected. The selecting is based on at least one of a spatial stream, a symbol, and a carrier frequency associated with the given sample. The selected data detection, technique is used to detect data of the given sample.

Abstract: Systems and methods for detecting data in a received multiple-input-multiple-output signal are provided. N signals are received from N antennas, with M being greater than or equal to three. The N signals form a vector y and are associated with M sets of data values, where the M sets of data values form a vector x. A channel matrix (H) is estimated, and a QR decomposition of the channel matrix is performed, such that H=QR. The vector y is transformed into a vector z according to z=QHy. The R matrix and the rotated signal vector z are transformed such that one or more elements of the R matrix having complex number values are set equal to zero. Distance values are calculated using the transformed vector z and the vector x. Log likelihood ratio (LLR) values are calculated based on the distance values.

Abstract: Systems and methods for detecting data in a received multiple-input-multiple-output signal are provided. N signals are received from N respective antennas, where the received signals are associated with (i) M sets of data values, (ii) a set of symbols, and (iii) a set of carrier frequencies. The N signals are formed into a received signal vector y, and one or more transformations are performed on the received signal vector y to obtain a transformed vector. A plurality of samples are formed from the transformed vector. For samples of the plurality of samples, a data detection technique of a plurality of data detection techniques is selected. The selecting is based on at least one of a spatial stream, a symbol, and a carrier frequency associated with the given sample. The selected data detection, technique is used to detect data of the given sample.

Abstract: Systems and methods for detecting data in a received multiple-input-multiple-output signal are provided. N signals are received from N antennas, with M being greater than or equal to three. The N signals form a vector y and are associated with M sets of data values, where the M sets of data values form a vector x. A channel matrix (H) is estimated, and a QR decomposition of the channel matrix is performed, such that H=QR. The vector y is transformed into a vector z according to z=QHy. The R matrix and the rotated signal vector z are transformed such that one or more elements of the R matrix having complex number values are set equal to zero. Distance values are calculated using the transformed vector z and the vector x. Log likelihood ratio (LLR) values are calculated based on the distance values.

Abstract: Systems and methods for detecting data in a received multiple-input-multiple-output signal are provided. First, second, and third signals are received and form a vector y. The received signals are associated with first, second, and third data values that form a vector x. A channel matrix (H) is received, and a QR decomposition of the channel matrix is performed, such that H=QR. The vector y is transformed into a vector z according to z=QHy. A distance value between the rector z and the vector x is determined for each possible third data value. A nearest constellation point is calculated based on a first of the possible third data values. The calculating step is repeated for each of the possible third data values to generate a set of constellation point triplets. The distance values are determined using the set of constellation point triplets.