287 research outputs found

    Rate-Splitting Robustness in Multi-Pair Massive MIMO Relay Systems

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    Relay systems improve both coverage and system capacity. Toward this direction, a full-duplex (FD) technology, being able to boost the spectral efficiency by transmitting and receiving simultaneously on the same frequency and time resources, is envisaged to play a key role in future networks. However, its benefits come at the expense of self-interference (SI) from their own transmit signal. At the same time, massive multiple-input massive multiple-output systems, bringing unconventionally many antennas, emerge as a promising technology with huge degrees-of-freedom. To this end, this paper considers a multi-pair decode-and-forward FD relay channel, where the relay station is deployed with a large number of antennas. Moreover, the rate-splitting (RS) transmission has recently been shown to provide significant performance benefits in various multi-user scenarios with imperfect channel state information at the transmitter (CSIT). Engaging the RS approach, we employ the deterministic equivalent analysis to derive the corresponding sum-rates in the presence of interferences. Initially, numerical results demonstrate the robustness of RS in half-duplex (HD) systems, since the achievable sum-rate increases without bound, i.e., it does not saturate at high signal-to-noise ratio. Next, we tackle the detrimental effect of SI in FD. In particular, and most importantly, not only FD outperforms HD, but also RS enables increasing the range of SI over which FD outperforms HD. Furthermore, increasing the number of relay station antennas, RS appears to be more efficacious due to imperfect CSIT, since SI decreases. Interestingly, increasing the number of users, the efficiency of RS worsens and its implementation becomes less favorable under these conditions. Finally, we verify that the proposed DEs, being accurate for a large number of relay station antennas, are tight approximations even for realistic system dimensions.Peer reviewedFinal Accepted Versio

    Hybrid Processing Design for Multipair Massive MIMO Relaying with Channel Spatial Correlation

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    Massive multiple-input multiple-output (MIMO) avails of simple transceiver design which can tackle many drawbacks of relay systems in terms of complicated signal processing, latency, and noise amplification. However, the cost and circuit complexity of having one radio frequency (RF) chain dedicated to each antenna element are prohibitive in practice. In this paper, we address this critical issue in amplify-and-forward (AF) relay systems using a hybrid analog and digital (A/D) transceiver structure. More specifically, leveraging the channel long-term properties, we design the analog beamformer which aims to minimize the channel estimation error and remain invariant over a long timescale. Then, the beamforming is completed by simple digital signal processing, i.e., maximum ratio combining/maximum ratio transmission (MRC/MRT) or zero-forcing (ZF) in the baseband domain. We present analytical bounds on the achievable spectral efficiency taking into account the spatial correlation and imperfect channel state information at the relay station. Our analytical results reveal that the hybrid A/D structure with ZF digital processor exploits spatial correlation and offers a higher spectral efficiency compared to the hybrid A/D structure with MRC/MRT scheme. Our numerical results showcase that the hybrid A/D beamforming design captures nearly 95% of the spectral efficiency of a fully digital AF relaying topology even by removing half of the RF chains. It is also shown that the hybrid A/D structure is robust to coarse quantization, and even with 2-bit resolution, the system can achieve more than 93% of the spectral efficiency offered by the same hybrid A/D topology with infinite resolution phase shifters.Comment: 17 pages, 13 figures, to appear in IEEE Transactions on Communication

    Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities

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    Recently there has been a flurry of research on the use of reconfigurable intelligent surfaces (RIS) in wireless networks to create smart radio environments. In a smart radio environment, surfaces are capable of manipulating the propagation of incident electromagnetic waves in a programmable manner to actively alter the channel realization, which turns the wireless channel into a controllable system block that can be optimized to improve overall system performance. In this article, we provide a tutorial overview of reconfigurable intelligent surfaces (RIS) for wireless communications. We describe the working principles of reconfigurable intelligent surfaces (RIS) and elaborate on different candidate implementations using metasurfaces and reflectarrays. We discuss the channel models suitable for both implementations and examine the feasibility of obtaining accurate channel estimates. Furthermore, we discuss the aspects that differentiate RIS optimization from precoding for traditional MIMO arrays highlighting both the arising challenges and the potential opportunities associated with this emerging technology. Finally, we present numerical results to illustrate the power of an RIS in shaping the key properties of a MIMO channel.Comment: to appear in the IEEE Transactions on Cognitive Communications and Networking (TCCN

    Physical Layer Service Integration in 5G: Potentials and Challenges

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    High transmission rate and secure communication have been identified as the key targets that need to be effectively addressed by fifth generation (5G) wireless systems. In this context, the concept of physical-layer security becomes attractive, as it can establish perfect security using only the characteristics of wireless medium. Nonetheless, to further increase the spectral efficiency, an emerging concept, termed physical-layer service integration (PHY-SI), has been recognized as an effective means. Its basic idea is to combine multiple coexisting services, i.e., multicast/broadcast service and confidential service, into one integral service for one-time transmission at the transmitter side. This article first provides a tutorial on typical PHY-SI models. Furthermore, we propose some state-of-the-art solutions to improve the overall performance of PHY-SI in certain important communication scenarios. In particular, we highlight the extension of several concepts borrowed from conventional single-service communications, such as artificial noise (AN), eigenmode transmission etc., to the scenario of PHY-SI. These techniques are shown to be effective in the design of reliable and robust PHY-SI schemes. Finally, several potential research directions are identified for future work.Comment: 12 pages, 7 figure

    Reconfigurable Intelligent Surface for Physical Layer Security in 6G-IoT: Designs, Issues, and Advances

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    Sixth-generation (6G) networks pose substantial security risks because confidential information is transmitted over wireless channels with a broadcast nature, and various attack vectors emerge. Physical layer security (PLS) exploits the dynamic characteristics of wireless environments to provide secure communications, while reconfigurable intelligent surfaces (RISs) can facilitate PLS by controlling wireless transmissions. With RIS-aided PLS, a lightweight security solution can be designed for low-end Internet of Things (IoT) devices, depending on the design scenario and communication objective. This article discusses RIS-aided PLS designs for 6G-IoT networks against eavesdropping and jamming attacks. The theoretical background and literature review of RIS-aided PLS are discussed, and design solutions related to resource allocation, beamforming, artificial noise, and cooperative communication are presented. We provide simulation results to show the effectiveness of RIS in terms of PLS. In addition, we examine the research issues and possible solutions for RIS modeling, channel modeling and estimation, optimization, and machine learning. Finally, we discuss recent advances, including STAR-RIS and malicious RIS.Comment: Accepted for IEEE Internet of Things Journa
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