The present disclosure provides a method (100) in a network device for channel estimation. The method (100) includes: transmitting (110) to a terminal device an instruction to precode each of a number, L, of DeModulation Reference Signals, DMRSs, using a number, N, of linearly independent precoders, respectively; receiving (120) from the terminal device L*N precoded DMRSs; estimating (130) an equivalent channel associated with an uplink channel from the terminal device to the network device based on one or more of the L*N precoded DMRSs; and determining (140) the uplink channel from the equivalent channel based on the N precoders.

Based on the receipt of a demodulation reference signal from a user equipment, a determination can be made by the network node that a demodulation reference signal configuration is not suitable for the condition of a transmission link between the network node and the user equipment. In response to this determination, the demodulation reference signal configuration can be modified.

Examples described herein include systems and methods which include wireless devices and systems with examples of full duplex compensation with a self-interference noise calculator. The self-interference noise calculator may be coupled to antennas of a wireless device and configured to generate adjusted signals that compensate self-interference. The self-interference noise calculator may include a network of processing elements configured to combine transmission signals into sets of intermediate results. Each set of intermediate results may be summed in the self-interference noise calculator to generate a corresponding adjusted signal. The adjusted signal is received by a corresponding wireless receiver to compensate for the self-interference noise generated by a wireless transmitter transmitting on the same frequency band as the wireless receiver is receiving.

Various embodiments provide for deep learning-based architectures and design methodologies for an orthogonal frequency division multiplexing (OFDM) receiver under the constraint of one-bit complex quantization. Single bit quantization greatly reduces complexity and power consumption in the receivers, but makes accurate channel estimation and data detection difficult. This is particularly true for OFDM waveforms, which have high peak-to average (signal power) ratio in the time domain and fragile subcarrier orthogonality in the frequency domain. The severe distortion for one-bit quantization typically results in an error floor even at moderately low signal-to-noise-ratio (SNR) such as 5 dB. For channel estimation (using pilots), various embodiments use novel generative supervised deep neural networks (DNNs) that can be trained with a reasonable number of pilots. After channel estimation, a neural network-based receiver specifically, an autoencoder jointly learns a precoder and decoder for data symbol detection.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a base station may transmit a message, to a user equipment (UE), instructing the UE to activate or update a reference signal (RS) corresponding to an uplink communication transmitted by the UE. The base station may communicate with the UE, after a time period, using a beam configuration of the base station that corresponds to a beam configuration of the UE for transmitting the RS, the time period being based at least in part on a determination of whether the UE identified the beam configuration of the base station. Numerous other aspects are provided.

A method for reporting a channel state in a wireless communication system according to an embodiment of the present disclosure may comprise the steps of: receiving a channel state report setting including an index of a first bandwidth part (BWP); receiving a trigger of a channel state report for a second BWP other than the first BWP; measuring a channel state in the second BWP in a measurement gap according to the trigger; and transmitting the measured channel state to a base station on an available uplink resource within a first activated BWP after the measurement gap.

A network control and rate optimization solution for multiuser multiple input multiple output (MU-MIMO) communications in wireless networks. This solution is decentralized and includes scheduling and routing of the MU-MIMO communication links that adapt to dynamic channel, interference, and traffic conditions. The ergodic sum rates of MIMO multiple access channel (MAC) and interference channel (IC) configurations are analyzed by considering the error, and overhead effects due to channel estimation (training) and quantization (feedback). By taking practical considerations such as channel estimation, quantization error and in-network interference into account, the rate gain is shown with an increasing number of antennas compared with single-input single-output (SISO) systems. A distributed channel access protocol to select and activate MU-MIMO configurations is presented with the maximum achievable sum rates using local information on channel, interference, and traffic conditions. The scheduling algorithm is extended to routing via a cross-layer solution based on a decentralized version of the backpressure algorithm. After accounting for the control message overhead, it is shown that the proposed MU-MIMO scheduling and routing solution improves the stable throughput over the minimum distance routing based on frequency of encounters and single user MIMO communications in a mobile ad hoc network (MANET) setting.

A method of configuring a preamble of a downlink frame for synchronization in data frame transmission of a 60 GHz wireless local area network system, the method comprising arranging a short preamble having a plurality of repetitive S symbols, and an IS symbol, and arranging a long preamble having a long cyclic prefix (CP) and a plurality of L symbols for frame synchronization and symbol timing by performing auto-correlation according to the length of window of the auto-correlation.

A high-speed serial interface is provided. In one aspect, the high-speed serial interface uses three phase modulation for jointly encoding data and clock information. Accordingly, the need for de-skewing circuitry at the receiving end of the interface is eliminated, resulting in reduced link start-up time and improved link efficiency and power consumption. In one embodiment, the high-speed serial interface uses fewer signal conductors than conventional systems having separate conductors for data and clock information. In another embodiment, the serial interface allows for data to be transmitted at any speed without the receiving end having prior knowledge of the transmission data rate. In another aspect, the high-speed serial interface uses polarity encoded three phase modulation for jointly encoding data and clock information. This further increases the link capacity of the serial interface by allowing for more than one bit to be transmitted in any single baud interval.

Method of scrambling signals, transmission point device, and user equipment using the method are provided. The method includes: sending an ID table to a user equipment through higher layer signaling, the ID table being a subset of the whole ID space and containing available IDs for the user equipment; notifying the user equipment an ID in the ID table to be used through physical layer signaling or UE specific higher layer signaling; generating a random seed based on the notified ID; initializing a scrambling sequence by the random seed; and scrambling the signals with the initialized scrambling sequence. The method of the disclosure, by combining physical layer signaling and higher layer signaling, may notify the used group ID and the blind detection space to a UE, wherein the blind detection for the UE is enabled and the signaling overhead is reduced.