As a key technology for 5G and beyond, Multi-User Multi-Input Multi-Output (MU-MIMO) can achieve Gbps downlink rate by allowing concurrent transmission from one Access Point (AP) to multiple users. However, the huge overhead of full CSI feedback may overwhelm the gain yielded by beamforming. Although there have been many works on compress CSI to reduce the feedback overhead, the performance of beamforming may decrease because the accuracy of channel state degrades. To address the tradeoff between feedback overhead and accuracy, we present a two-stage Multipath Profile based Feedback protocol (MPF). In the first stage, compared with CSI feedback, the channel state is represented by multipath profile which has a smaller size but is accurate enough for user selection. Meanwhile, we propose an implicit polling scheme to decrease the feedback further. In the second stage, only the selected users send their CSI information to the AP to guarantee the low overhead and accuracy of steering matrix calculation. We implement and evaluate MPF with USRP N210. Experiments show that MPF can outperform alternative schemes in a variety of radio environments.

The transmission on fronthaul links in the cloud radio access network has become a bottleneck with the increasing data rate. In this paper, we propose a novel two-stage compression scheme for fronthaul links. In the first stage, the commonly used techniques like cyclic prefix stripping and sampling rate adaptation are implemented. In the second stage, a structure called linear prediction coding with decision threshold (LPC-DT) is proposed to remove the redundancies of signal. Considering that the linear prediction outputs have large dynamic range, a two-piecewise quantization with optimized decision threshold is applied to enhance the quantization performance. In order to further lower the transmission rate, a multi-level successive structure of lossless polar source coding is proposed to compress the quantization output with low encoding and decoding complexity. Simulation results demonstrate that the proposed scheme with LPC-DT and LPSC offers not only significantly better compression ratios but also more flexibility in bandwidth settings compared with traditional ones.

Dichotomous coordinate descent (DCD) iterations method has been proposed for adaptive feedback cancellation, which uses a fixed number of iterations and a fixed amplitude range. In this paper, improved DCD algorithms are proposed, which substitute the constant number of iterations and the amplitude range with a variable number of iterations(VI) and/or a variable amplitude range(VA). Thus VI-DCD, VA-DCD and VIA-DCD algorithms are obtained. Computer simulations are used to compare the performance of the proposed algorithms against original DCD algorithm, and simulation results demonstrate that significant improvements are achieved in the convergence speed and accuracy. Another notable conclusion by further simulations is that the proposed algorithms achieve superior performance with a real speech segment as the input.

With no need for Road Side Unit (RSU), multi-hop Vehicular Ad Hoc NETworks (VANETs) have drawn more and more attention recently. Considering the safety of vehicles, a Media Access Control (MAC) protocol for reliable transmission is critical for multi-hop VANETs. Most current works need RSU to handle the collisions brought by hidden-terminal problem and the mobility of vehicles. In this paper, we proposed RV-MAC, which is a reliable MAC protocol for multi-hop VANETs based on Time Division Multiple Access (TDMA). First, to address the hidden-terminal under the networks with multi-hop topology, we design a region marking scheme to divide vehicles into different regions. Then a collisions avoidance scheme is proposed to handle the collisions owing to channel competition and the mobility of vehicles. Simulation results show that compared with other protocol, RV-MAC can decrease contention collisions by 30% and encounter collisions by 50% respectively. As a result, RV-MAC achieves higher throughput and lower network delay.

In this paper, we propose a low-complexity widely-linear minimum mean square error (WL-MMSE) signal detection based on the Chebyshev polynomials accelerated symmetric successive over relaxation (SSORcheb) algorithm for uplink (UL) over-loaded large-scale multiple-input multiple-output (MIMO) systems. The technique of utilizing Chebyshev acceleration not only speeds up the convergence rate significantly, and maximizes the data throughput, but also reduces the cost. By utilizing the random matrix theory, we present good estimates for the Chebyshev acceleration parameters of the proposed signal detection in real large-scale MIMO systems. Simulation results demonstrate that the new WL-SSORcheb-MMSE detection not only outperforms the recently proposed linear iterative detection, and the optimal polynomial expansion (PE) WL-MMSE detection, but also achieves a performance close to the exact WL-MMSE detection. Additionally, the proposed detection offers superior sum rate and bit error rate (BER) performance compared to the precision MMSE detection with substantially fewer arithmetic operations in a short coherence time. Therefore, the proposed detection can satisfy the high-density and high-mobility requirements of some of the emerging wireless networks, such as, the high-mobility Internet of Things (IoT) networks.

Media Access Control (MAC) is critical to guarantee different Quality of Service (QoS) requirements for Unmanned Aerial Vehicle (UAV) networks, such as high reliability for safety packets and high throughput for service packets. Meanwhile, due to their ability to provide lower delay and higher data rates, more UAVs are using frequently directional antennas. However, it is challenging to support different QoS in UAV networks with directional antennas, because of the high mobility of UAV which causes serious channel resource loss. In this paper, we propose CU-MAC which is a MAC protocol for Centralized UAV networks with directional antennas. First, we design a mobility prediction based time-frame optimization scheme to provide reliable broadcast service for safety packets. Then, a traffic prediction based channel allocation scheme is proposed to guarantee the priority of video packets which are the most common service packets nowadays. Simulation results show that compared with other representative protocols, CU-MAC achieves higher reliability for safety packets and improves the throughput of service packets, especially video packets.