This paper presents an overview of the theory and currently known techniques for multi-cell MIMO (multiple input multiple output) cooperation in wireless networks. In dense networks where interference emerges as the key capacity-limiting factor, multi-cell cooperation can dramatically improve the system performance. Remarkably, such techniques literally exploit inter-cell interference by allowing the user data to be jointly processed by several interfering base stations, thus mimicking the benefits of a large virtual MIMO array. Multi-cell MIMO cooperation concepts are examined from different perspectives, including an examination of the fundamental information-theoretic limits, a review of the coding and signal processing algorithmic developments, and, going beyond that, consideration of very practical issues related to scalability and system-level integration. A few promising and quite fundamental research avenues are also suggested.

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Multi-Cell MIMO Cooperative Networks: A New Look at Interference

It is now well known that employing channel adaptive signaling in wireless communication systems can yield large improvements in almost any performance metric. Unfortunately, many kinds of channel adaptive techniques have been deemed impractical in the past because of the problem of obtaining channel knowledge at the transmitter. The transmitter in many systems (such as those using frequency division duplexing) can not leverage techniques such as training to obtain channel state information. Over the last few years, research has repeatedly shown that allowing the receiver to send a small number of information bits about the channel conditions to the transmitter can allow near optimal channel adaptation. These practical systems, which are commonly referred to as limited or finite-rate feedback systems, supply benefits nearly identical to unrealizable perfect transmitter channel knowledge systems when they are judiciously designed. In this tutorial, we provide a broad look at the field of limited feedback wireless communications. We review work in systems using various combinations of single antenna, multiple antenna, narrowband, broadband, single-user, and multiuser technology. We also provide a synopsis of the role of limited feedback in the standardization of next generation wireless systems.

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An overview of limited feedback in wireless communication systems

Massive multiple-input multiple-output MIMO is one of themost promising technologies for the next generation of wirelesscommunication networks because it has the potential to providegame-changing improvements in spectral efficiency SE and energyefficiency EE. This monograph summarizes many years ofresearch insights in a clear and self-contained way and providesthe reader with the necessary knowledge and mathematical toolsto carry out independent research in this area. Starting froma rigorous definition of Massive MIMO, the monograph coversthe important aspects of channel estimation, SE, EE, hardwareefficiency HE, and various practical deployment considerations.From the beginning, a very general, yet tractable, canonical systemmodel with spatial channel correlation is introduced. This modelis used to realistically assess the SE and EE, and is later extendedto also include the impact of hardware impairments. Owing tothis rigorous modeling approach, a lot of classic "wisdom" aboutMassive MIMO, based on too simplistic system models, is shownto be questionable.

https://www.nowpublishers.com/article/DownloadSummary/SIG-093

Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency

In a conventional wireless cellular system, signal processing is performed on a per-cell basis; out-of-cell interference is treated as background noise. This paper considers the benefit of coordinating base-stations across multiple cells in a multi-antenna beamforming system, where multiple base-stations may jointly optimize their respective beamformers to improve the overall system performance. Consider a multicell downlink scenario where base-stations are equipped with multiple transmit antennas employing either linear beamforming or nonlinear dirty-paper coding, and where remote users are equipped with a single antenna each, but where multiple remote users may be active simultaneously in each cell. This paper focuses on the design criteria of minimizing either the total weighted transmitted power or the maximum per-antenna power across the base-stations subject to signal-to-interference-and-noise-ratio (SINR) constraints at the remote users. The main contribution of the paper is an efficient algorithm for finding the joint globally optimal beamformers across all base-stations. The proposed algorithm is based on a generalization of uplink-downlink duality to the multicell setting using the Lagrangian duality theory. An important feature is that it naturally leads to a distributed implementation in time-division duplex (TDD) systems. Simulation results suggest that coordinating the beamforming vectors alone already provide appreciable performance improvements as compared to the conventional per-cell optimized network.

/pdf/coordinated-beamforming-for-the-multicell-multi-antenna-2hdgwj1tq8.pdf

Coordinated beamforming for the multicell multi-antenna wireless system

6G and beyond will fulfill the requirements of a fully connected world and provide ubiquitous wireless connectivity for all. Transformative solutions are expected to drive the surge for accommodating a rapidly growing number of intelligent devices and services. Major technological breakthroughs to achieve connectivity goals within 6G include: (i) a network operating at the THz band with much wider spectrum resources, (ii) intelligent communication environments that enable a wireless propagation environment with active signal transmission and reception, (iii) pervasive artificial intelligence, (iv) large-scale network automation, (v) an all-spectrum reconfigurable front-end for dynamic spectrum access, (vi) ambient backscatter communications for energy savings, (vii) the Internet of Space Things enabled by CubeSats and UAVs, and (viii) cell-free massive MIMO communication networks. In this roadmap paper, use cases for these enabling techniques as well as recent advancements on related topics are highlighted, and open problems with possible solutions are discussed, followed by a development timeline outlining the worldwide efforts in the realization of 6G. Going beyond 6G, promising early-stage technologies such as the Internet of NanoThings, the Internet of BioNanoThings, and quantum communications, which are expected to have a far-reaching impact on wireless communications, have also been discussed at length in this paper.

/pdf/6g-and-beyond-the-future-of-wireless-communications-systems-3jqy8nx3qf.pdf

6G and Beyond: The Future of Wireless Communications Systems

Base station cooperation is an attractive way of increasing the spectral efficiency in multiantenna communication. By serving each terminal through several base stations in a given area, intercell interference can be coordinated and higher performance achieved, especially for terminals at cell edges. Most previous work in the area has assumed that base stations have common knowledge of both data dedicated to all terminals and full or partial channel state information (CSI) of all links. Herein, we analyze the case of distributed cooperation where each base station has only local CSI, either instantaneous or statistical. In the case of instantaneous CSI, the beamforming vectors that can attain the outer boundary of the achievable rate region are characterized for an arbitrary number of multiantenna transmitters and single-antenna receivers. This characterization only requires local CSI and justifies distributed precoding design based on a novel virtual signal-to-interference noise ratio (SINR) framework, which can handle an arbitrary SNR and achieves the optimal multiplexing gain. The local power allocation between terminals is solved heuristically. Conceptually, analogous results for the achievable rate region characterization and precoding design are derived in the case of local statistical CSI. The benefits of distributed cooperative transmission are illustrated numerically, and it is shown that most of the performance with centralized cooperation can be obtained using only local CSI.

/pdf/cooperative-multicell-precoding-rate-region-characterization-1ttc6f47xj.pdf

Cooperative Multicell Precoding: Rate Region Characterization and Distributed Strategies With Instantaneous and Statistical CSI

In this letter, we address the problem of distributed multi-antenna cooperative transmission in a cellular system. Most research in this area has so far assumed that base stations not only have the data dedicated to all the users but also share the full channel state information (CSI). In what follows, we assume that each base station (BS) only has local CSI knowledge. We propose a suboptimal, yet efficient, way in which the multicell MISO precoders may be designed at each BS in a distributed manner, as a superposition of so-called virtual SINR maximizations: a virtual SINR maximizing transmission scheme yields Pareto optimal rates for the MISO Interference Channel (IC); its extension to the multicell MISO channel is shown to provide a distributed precoding scheme achieving a certain fairness optimality for the two link case. We illustrate the performance of our algorithm through Monte Carlo simulations.

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Distributed Multicell-MISO Precoding Using the Layered Virtual SINR Framework

We consider a multi-pair two-way relay channel (TWRC) where the single-antenna mobile terminals (MT) on each pair seek to communicate, and can do so, via a common multiple antenna relay station (RS). In the multi-pair TWRC, the main bottleneck on system performance is the interference seen by each MT due to the other communicating MT pairs. In this paper, we try to tackle this problem in the spatial domain by using multiple antennas at the RS. Considering Amplify-and-Forward (AF) and Quantize-and-Forward (QF) relaying strategies, different transmit/receive beamforming schemes at the RS are proposed. We compare our proposed schemes to each other and to the Decode-and-Forward (DF) relaying strategy with achievable sum rate taken as a performance metric and show that in a wide range of signal-to-noise ratio (SNR) our schemes outperform the DF relaying strategy.

/pdf/multi-pair-two-way-relay-channel-with-multiple-antenna-relay-102ny62xz6.pdf

Multi-Pair Two-Way Relay Channel with Multiple Antenna Relay Station

Coordination in a multi-cell/link environment has been attracting a lot of attention in the research community recently. In this paper, we consider the problem of coordinated beamforming where base stations (BS) equipped with multiple antennas attempt to serve a separate user each despite the interference generated by the other bases. We propose a framework for a distributed optimization of the beamformers at each base, where distributed is defined as using "local CSIT" only. We present and compare two distributed approaches (one iterative and another direct approach) which have in common the optimization of the beamformers as a combination of so-called egoistic and altruistic solutions for this problem. We provide the intuitions behind these approaches and some theoretical grounds for optimality in certain cases. Performance is finally illustrated through numerical simulations.

/pdf/distributed-beamforming-coordination-in-multicell-mimo-596jpbqtvt.pdf

Distributed Beamforming Coordination in Multicell MIMO Channels

We consider the downlink of a multiuser MIMO channel, corresponding to a single cell with an Nt-antenna base station and K single-antenna mobile terminals (MTs). It is known that when full channel state information (CSI) is available at the transmitter (full CSIT) the capacity of the system scales as Nt log(P/Nt- log K), under a total power constraint P [1], While, when the transmitter has no CSI, scaling reduces to that of a TDMA system. This paper examines the more realistic case of having an intermediate state of CSI. The key idea is based on a split of the allotted feedback between two stages: A first stage devoted to scheduling followed by a second stage for precoder design for the selected users. Based on an approximation of the achievable sum rate, we introduce a method for determining the splitting of the feedback rate so as to maximize performance and provide intuitions. We illustrate the gains of the 2-stage approach via Monte Carlo simulations.

/pdf/a-two-stage-approach-to-feedback-design-in-multi-user-mimo-4cmdr381zt.pdf

Randa Zakhour

Papers

Cooperative Multicell Precoding: Rate Region Characterization and Distributed Strategies With Instantaneous and Statistical CSI

Distributed Multicell-MISO Precoding Using the Layered Virtual SINR Framework

Multi-Pair Two-Way Relay Channel with Multiple Antenna Relay Station

Distributed Beamforming Coordination in Multicell MIMO Channels

A Two-Stage Approach to Feedback Design in Multi-User MIMO Channels with Limited Channel State Information