Intelligent Reflecting Surface Assisted Massive MIMO Communications

In a practical massive MIMO (multiple-input multiple-output) system, the number of antennas at a base station (BS) is constrained by the space and cost factors, which limits the throughput gain promised by theoretical analysis. This paper thus studies the feasibility of adopting the intelligent reflecting surface (IRS) to further improve the beamforming gain of the uplink communications in a massive MIMO system. Under such a novel system, the central question lies in whether the IRS is able to enhance the network throughput as expected, if the channel estimation overhead is taken into account. In this paper, we first show that the favorable propagation property for the conventional massive MIMO system without IRS, i.e., the channels of arbitrary two users are orthogonal, no longer holds for the IRS-assisted massive MIMO system, due to its special channel property that each IRS element reflects the signals from all the users to the BS via the same channel. As a result, the maximal-ratio combining (MRC) receive beamforming strategy leads to strong inter-user interference and thus even lower user rates than those of the massive MIMO system without IRS. To tackle this challenge, we propose a novel strategy for zero-forcing (ZF) beamforming design at the BS and reflection coefficients design at the IRS to efficiently null the inter-user interference. Under our proposed strategy, it is rigorously shown that even if the channel estimation overhead is considered, the IRS-assisted massive MIMO system can always achieve higher throughput compared to its counterpart without IRS, despite the fact that the favorable propagation property no longer holds.Comment: Invited paper, accepted by IEEE SPAWC 202

An Orchestration Framework for Open System Models of Reconfigurable Intelligent Surfaces

To obviate the control of reflective intelligent surfaces (RISs) and the related control overhead, recent works envisioned autonomous and self-configuring RISs that do not need explicit use of control channels. Instead, these devices, named hybrid RISs (HRISs), are equipped with receiving radio-frequency (RF) chains and can perform sensing operations to act independently and in parallel to the other network entities. A natural problem then emerges: as the HRIS operates concurrently with the communication protocols, how should its operation modes be scheduled in time such that it helps the network while minimizing any undesirable effects? In this paper, we propose an orchestration framework that answers this question revealing an engineering trade-off, called the self-configuring trade-off, that characterizes the applicability of self-configuring HRISs under the consideration of massive multiple-input multiple-output (mMIMO) networks. We evaluate our proposed framework considering two different HRIS hardware architectures, the power- and signal-based HRISs that differ in their hardware complexity. The numerical results show that the self-configuring HRIS can offer significant performance gains when adopting our framework.Comment: 31 pages, 7 figures, submitted to an IEEE journa

Reconfigurable Intelligent Surfaces for Smart Cities: Research Challenges and Opportunities

The concept of Smart Cities has been introduced as a way to benefit from the digitization of various ecosystems at a city level. To support this concept, future communication networks need to be carefully designed with respect to the city infrastructure and utilization of resources. Recently, the idea of 'smart' environment, which takes advantage of the infrastructure for better performance of wireless networks, has been proposed. This idea is aligned with the recent advances in design of reconfigurable intelligent surfaces (RISs), which are planar structures with the capability to reflect impinging electromagnetic waves toward preferred directions. Thus, RISs are expected to provide the necessary flexibility for the design of the 'smart' communication environment, which can be optimally shaped to enable cost- and energy-efficient signal transmissions where needed. Upon deployment of RISs, the ecosystem of the Smart Cities would become even more controllable and adaptable, which would subsequently ease the implementation of future communication networks in urban areas and boost the interconnection among private households and public services. In this paper, we describe our vision of the application of RISs in future Smart Cities. In particular, the research challenges and opportunities are addressed. The contribution paves the road to a systematic design of RIS-assisted communication networks for Smart Cities in the years to come.Comment: Submitted for possible publication in IEEE Open Journal of the Communications Societ

Power Scaling Law Analysis and Phase Shift Optimization of RIS-aided Massive MIMO Systems with Statistical CSI

This paper considers an uplink reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) system, where the phase shifts of the RIS are designed relying on statistical channel state information (CSI). Considering the complex environment, the general Rician channel model is adopted for both the users-RIS links and RIS-BS links. We first derive the closed-form approximate expressions for the achievable rate which holds for arbitrary numbers of base station (BS) antennas and RIS elements. Then, we utilize the derived expressions to provide some insights, including the asymptotic rate performance, the power scaling laws, and the impacts of various system parameters on the achievable rate. We also tackle the sum-rate maximization and the minimum user rate maximization problems by optimizing the phase shifts at the RIS based on genetic algorithm (GA). Finally, extensive simulations are provided to validate the benefits by integrating RIS into conventional massive MIMO systems. Our simulations also demonstrate the feasibility of deploying large-size but low-resolution RIS in massive MIMO systems

Intelligent reflecting surface assisted massive MIMO communications

2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 26-29 May 2020, Atlanta, GA, USA202404 bckwAuthor’s OriginalSelf-fundedPublishedGreen (AO