Reconfigurable intelligent surface (RIS) has recently drawn intensive attention due to its potential of simultaneously realizing high spectral and energy efficiency in a sustainable way. This paper focuses on the design of efficient transmission methods to maximize the uplink sum throughput in a RIS-aided multi-user multi-input multi-output (MU-MIMO) system. To provide an insightful basis, the channel capacity of RIS-aided MU-MIMO is theoretically analyzed. Then, the conventional transmission schemes based on orthogonal multiple access are presented as the baseline. From the information-theoretic perspective, we propose two novel schemes, i.e., \textit{joint transmission} based on the semidefinite relaxation of quadratic optimization problems and \textit{opportunistic transmission} relying on the best user selection. The superiority of the proposed schemes over the conventional ones in terms of achievable rates is justified through simulation results.

Intelligent reflecting surface (IRS) is envisioned to become a key technology for the upcoming six-generation (6G) wireless system due to its potential of reaping high performance in a power-efficient and cost-efficient way. With its disruptive capability and hardware constraint, the integration of IRS imposes some fundamental particularities on the coordination of multi-user signal transmission. Consequently, the conventional orthogonal and non-orthogonal multiple-access schemes are hard to directly apply because of the joint optimization of active beamforming at the base station and passive reflection at the IRS.  Relying on an alternating optimization method, we develop novel schemes for efficient multiple access in IRS-aided multi-user multi-antenna systems in this paper. Achievable performance in terms of the sum spectral efficiency is theoretically analyzed. A comprehensive comparison of different schemes and configurations is conducted through Monte-Carlo simulations to clarify which scheme is favorable for this emerging 6G paradigm.

Reconfigurable intelligent surface a.k.a intelligent reflecting surface (IRS) has recently drawn considerable attention because of its potential to achieve high spectral and energy efficiencies in a cost-effective way. Due to its disruptive ability to manipulate wireless environments, IRS imposes fundamental particularities on multi-user communications. This paper focuses on studying  orthogonal and non-orthogonal multiple access in IRS-aided systems. Unlike most prior works assuming continuous phase shifts, we employ the practical setup where only a finite number of discrete phase shifts are available. To maximize the sum rate, active beamforming and discrete reflection need to be jointly optimized. We therefore propose an alternative optimization method to get the optimal continuous phase shifts iteratively, and then quantize each phase shift to its nearest discrete value. The sum-rate maximization of different schemes is theoretically analyzed and numerically evaluated with different numbers of phase-control bits.

This paper focuses on multi-user downlink signal transmission in a wireless system aided by multiple reconfigurable intelligent surfaces (RISs). In such a multi-RIS, multi-user, multi-antenna scenario, determining a set of RIS phase shifts to maximize the sum throughput becomes intractable.  Hence, we propose a novel scheme that can substantially simplify the optimization of passive beamforming. By opportunistically selecting a user with the best channel condition as the only active transmitter in the system, it degrades to single-user passive beamforming,  where two methods, i.e., joint optimization based on the semidefinite relaxation approach and alternating optimization, are applicable. The superiority of the proposed scheme is demonstrated through Monte-Carlo simulations.

Intelligent reflecting surface (IRS) has recently received much attention from the research community due to its potential to achieve high spectral and power efficiency cost-effectively. In addition to traditional cellular networks, the use of IRS in vehicular networks is also considered. Prior works on IRS-aided vehicle-to-everything communications focus on deploying reflection surfaces on the facades of buildings along the road for sidelink performance enhancement. This paper goes beyond the state of the art by presenting a novel paradigm coined Intelligent Reflecting Vehicle Surface (IRVS). It embeds a massive number of reflection elements on vehicles’ surfaces to aid moving vehicular networks in military and emergency communications. We propose an alternative optimization method to optimize jointly active beamforming at the base station and passive reflection across multiple randomly-distributed vehicle surfaces. Performance evaluation in terms of sum spectral efficiency under continuous, discrete, and random phase shifts is conducted. Numerical results reveal that IRVS can substantially improve the capacity of a moving vehicular network.

In the context of cell-free massive multi-input multi-output (CFmMIMO), zero-forcing precoding (ZFP) is superior in terms of spectral efficiency. However, it suffers from channel aging owing to fronthaul and processing delays. In this paper,  we propose a robust scheme coined delay-tolerant zero-forcing precoding (DT-ZFP), which exploits deep learning-aided channel prediction to alleviate the effect of outdated channel state information (CSI). A predictor consisting of a bank of user-specific predictive modules is specifically designed for such a multi-user scenario. Leveraging the degree of freedom brought by the prediction horizon, the delivery of CSI and precoded data through a fronthaul network and the transmission of user data and pilots over an air interface can be parallelized. Therefore,  DT-ZFP not only effectively combats channel aging but also avoids the inefficient Stop-and-Wait mechanism of the canonical ZFP in CFmMIMO.

This paper aims to clarify the impact of channel aging and phase noise on the performance of intelligent reflecting surface-aided wireless systems. We first model mathematically the outdated channel state information (CSI) due to Doppler shifts and phase noise stemming from hardware impairment. Then, a closed-form expression of achievable spectral efficiency under noisy and aged CSI is theoretically derived. Some typical simulation results to numerically demonstrate the performance impact are illustrated.

Exploiting the degree of freedom in the frequency domain and the near-far effect among different access points (APs), this paper proposes an opportunistic transmission scheme in cell-free massive MIMO-OFDM systems. The key idea is to orthogonally assign subcarriers among different users, so that there is only one user on each subcarrier. Then, a user is only served by its near APs through opportunistic selection, while the far APs are deactivated to avoid wasting power over their channels with severe propagation losses. Moreover, the number of active APs per subcarrier becomes small due to the opportunistic selection, making the use of downlink pilots and coherent detection feasible. As corroborated by numerical results, the proposed scheme can bring a significant performance boost in terms of both power efficiency and spectral efficiency.

In order to achieve a unprecedented terabits-per-second (Tbps) data rate in the sixth-generation (6G) mobile system, wireless communications require far more bandwidth, which cannot be available under the current spectrum-usage paradigm. Therefore, the 6G system has to exploit the abundant spectrum in the high-frequency bands, i.e., millimeter wave and terahertz (THz) frequencies. However, high-frequency transmission heavily relies on high beamforming gain to compensate for severe propagation loss and to extend its transmission distance. A beam-based system faces a barrier in the process of initial access, where a base station must broadcast synchronization signals and system information to all users within its coverage. Hence, this paper aims to propose a novel omnidirectional coverage scheme for THz communications with hybrid beamforming. It provides an instantaneously equal gain over all directions by forming complementary beams over sub-arrays. Numerical results verify that it can achieve omnidirectional coverage with a performance that remarkably outperforms the previous scheme.

To realize a unprecedentedly high data speed in terabits-per-second (Tbps), the upcoming sixth-generation (6G) mobile communications system needs to utilize the abundant spectrum in the terahertz bands. However, high-frequency transmission suffers severe propagation loss and short transmission distance, which would be heavily relies on a large-scale antenna array to reap high beamforming gain, used to compensate for such a loss. But beamforming over an antenna array, especially a large-scale array, raises a problem of omni-directional coverage during the phase of initial access, where a base station is required to broadcast synchronization signals and master system information to each user within its coverage. Therefore, this paper aims to propose a novel omni-directional beamforming scheme, providing instantaneous gain equally in all directions by forming a pair of complementary beams. Numerical results verify that it can achieve omni-directional coverage with the optimal performance that remarkably outperforms the previous scheme called random beamforming.

Complexity and heterogeneity of the fifth generation (5G) and beyond mobile systems impose a great challenge on current network managing approaches, which are vulnerable, time-consuming and costly. The state-of-the-art research direction in this field is to apply machine learning (ML) techniques to realize intelligent and highly self-organized networking. Unlike the physical layer, theoretical analyses and numerical simulations on the management layer are generally infeasible or not scientifically rigorous enough. Therefore, in this paper, we present a software-defined and virtualized wireless test-bed that is established to evaluate ML-based network management. Based on open-source software and off-the-shelf hardware, this test-bed is easily reproducible, which in turn is hopeful to foster innovative works in this field.

A document by Wei Jiang . Click on the document to view its contents.