Methods, systems, and devices for wireless communications are described. Some wireless communications systems may utilize beamforming techniques to process wireless communications transmitted in millimeter wave (mmW) frequency ranges. In such cases, a user equipment (UE) may perform lattice reduction (LR)-based preprocessing for a received resource element (RE), which allows the UE to utilize demapping techniques (e.g., minimum mean square error (MMSE)-based demapping techniques or successive interference cancellation (SIC) demapping techniques) that are less computationally-complex than conventional demapping techniques (e.g., maximum likelihood (ML)-based demapping techniques) while providing a similar performance as conventional techniques. Further, due to mmW systems' robustness to time-dispersion, the UE may apply the same LR to multiple REs across multiple symbols in the time domain and across multiple sub-carriers in the frequency domain. The computational cost of performing the LR calculation may be spread across multiple REs and further increase the efficiency of utilizing low-complexity demapping techniques.

Embodiments are presented herein of apparatuses, systems, and methods for a wireless device to perform sensing applications using communication signals. The first wireless device may determine to perform a sensing application and to perform the sensing application using a communication signal to be transmitted to a second device. In other words, the first wireless device may use a transmission that is scheduled for communication purposes to additionally perform sensing of one or more types. Example sensing or radar-like applications include estimating distance, motion, and/or angle to one or more objects or structures in the vicinity of the first wireless device. After transmitting the communication signal to the second wireless device, the first wireless device may receive a reflection of the communication signal. The first wireless device may use the reflection to perform the sensing application.

Disclosed is a method performed by a RRU of a distributed base station system of a wireless communication network, the RRU being connected to a BBU over a fronthaul link, the RRU being connected to N antennas. The method comprises obtaining uplink signals as received at the antennas from UEs wirelessly connected to the RRU, and obtaining a channel estimation matrix of wireless communication channels between UEs and the antennas. The method further comprises determining an error estimation matrix based on the channel estimation matrix, and on received reference signals y.sub.ref,l, the received reference signals having L symbols, L being smaller than N, determining intermediate signals, based on the uplink signals, the channel estimation matrix and the error estimation matrix, and sending to the BBU over the fronthaul link, the determined intermediate signals.

A method for minimizing a time domain mean square error (MSE) of channel estimation (CE) includes estimating, by a processor, a power delay profile (PDP) from a time domain observation of reference signal (RS) channels; estimating, by the processor, a noise variance of the RS channels; and determining, by the processor, a first arrival path (FAP) value and a delay spread estimation (DSE) value based on the estimated PDP and the estimated noise variance for minimizing the MSE of CE.

A method for estimating a wireless communication channel between a transmitter and a receiver, including a plurality of paths for propagation of a wave, at least one of the transmitter and the receiver being formed of a plurality of antennas. The method includes: for at least one path, determining a characteristic matrix, which depends on a first element representative of at least one propagation direction associated with the path, and a second element representative of a propagation distance associated with the path; and estimating the communication channel from the at least one obtained characteristic matrix.

A method for improving performance of an uplink non-orthogonal multiple access system under imperfect received user power control. The method is based on a plurality of user-specific transmitter filters assigned to a plurality of users. At a transmitter of each user, a signal to be transmitted according to the uplink non-orthogonal multiple access (NOMA) method is filtered by a unique filter assigned to a corresponding user, and then a baseband-to-RF processing is performed onto a symbol sequence to generate a transmitted signal. Each user transmits their respective signal using a same time-frequency resource, and receiver receives a superimposed signal which is transmitted through a plurality of respective uplink channels under imperfect received power control. An RF-to-baseband conversion is applied onto a received superimposed signal. Then, a receiver signal detection module; including an interference-cancellation multi-user detector detects each user data using knowledge of a plurality of transmitter filters of each user.

A channel estimation method. For at least one temporal difference observed between two sub-sequences of channel measurements, or channel estimations, consisting of complex vectors or scalars, the method includes: a first extrapolation on the basis of channel measurements or channel estimations of the sub-sequence preceding the temporal difference, going forward in time; a second extrapolation on the basis of channel measurements or channel estimations of the sub-sequence following the temporal difference, going backward in time; and calculation of a weighted average of the extrapolated estimations or measurements forward in time and of the extrapolated estimations or measurements backward in time, in order to obtain channel measurements or channel estimations regularly spaced apart in the temporal difference. The method is suitable for radio communications between a base station and a moving connected vehicle.

There are provided systems, methods, and interfaces for optimization of the fronthaul interface bandwidth for Radio Access Networks and Cloud Radio Access Networks.

A clock data recovery (CDR) mechanism qualifies symbols received from the data detector prior to using those symbols to compute a timing gradient. The disclosed CDR mechanism analyzes one or more recently received symbols to determine whether the current symbol should be used in computing the time gradient. When configured with a Mueller-Muller phase detector, the timing gradient for the received signal is set to zero if the current symbol is a −2 or a +2 and the previous symbol is non-zero. Otherwise, the Mueller-Muller timing gradient is evaluated in the traditional manner. When configured with a minimum mean-squared error phase detector, the timing gradient for the received signal is set to zero if the previous symbol is non-zero. Otherwise, the minimum mean-squared error timing gradient is evaluated in the traditional manner.

An adaptive equalizer includes a sample buffer that temporarily stores data obtained by fractional sampling at a sampling rate that is larger than one time and smaller than two times a symbol rate; and a processor coupled to the sample buffer and configured to: specify position of a training sequence in the data based on a correlation value between a first set of (f×T) samples and a second set of (f×T) samples following the first set of samples, assuming that the sampling rate is f, and a symbol length of a code pattern included in the training sequence inserted in the data is T, and calculate an initial value of a tap coefficient set to a tap of an adaptive equalization filter based on the specified training sequence, wherein the symbol length is set to be changeable so that f×T is an integer.