Wireless Communications

What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.

What Will 5G Be

A cellular base station serves a multiplicity of single-antenna terminals over the same time-frequency interval. Time-division duplex operation combined with reverse-link pilots enables the base station to estimate the reciprocal forward- and reverse-link channels. The conjugate-transpose of the channel estimates are used as a linear precoder and combiner respectively on the forward and reverse links. Propagation, unknown to both terminals and base station, comprises fast fading, log-normal shadow fading, and geometric attenuation. In the limit of an infinite number of antennas a complete multi-cellular analysis, which accounts for inter-cellular interference and the overhead and errors associated with channel-state information, yields a number of mathematically exact conclusions and points to a desirable direction towards which cellular wireless could evolve. In particular the effects of uncorrelated noise and fast fading vanish, throughput and the number of terminals are independent of the size of the cells, spectral efficiency is independent of bandwidth, and the required transmitted energy per bit vanishes. The only remaining impairment is inter-cellular interference caused by re-use of the pilot sequences in other cells (pilot contamination) which does not vanish with unlimited number of antennas.

Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas

Multi-user MIMO offers big advantages over conventional point-to-point MIMO: it works with cheap single-antenna terminals, a rich scattering environment is not required, and resource allocation is simplified because every active terminal utilizes all of the time-frequency bins. However, multi-user MIMO, as originally envisioned, with roughly equal numbers of service antennas and terminals and frequency-division duplex operation, is not a scalable technology. Massive MIMO (also known as large-scale antenna systems, very large MIMO, hyper MIMO, full-dimension MIMO, and ARGOS) makes a clean break with current practice through the use of a large excess of service antennas over active terminals and time-division duplex operation. Extra antennas help by focusing energy into ever smaller regions of space to bring huge improvements in throughput and radiated energy efficiency. Other benefits of massive MIMO include extensive use of inexpensive low-power components, reduced latency, simplification of the MAC layer, and robustness against intentional jamming. The anticipated throughput depends on the propagation environment providing asymptotically orthogonal channels to the terminals, but so far experiments have not disclosed any limitations in this regard. While massive MIMO renders many traditional research problems irrelevant, it uncovers entirely new problems that urgently need attention: the challenge of making many low-cost low-precision components that work effectively together, acquisition and synchronization for newly joined terminals, the exploitation of extra degrees of freedom provided by the excess of service antennas, reducing internal power consumption to achieve total energy efficiency reductions, and finding new deployment scenarios. This article presents an overview of the massive MIMO concept and contemporary research on the topic.

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Massive MIMO for next generation wireless systems

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In this paper, a novel covariance-based channel feedback mechanism is investigated for frequency division duplexing (FDD) massive multi-input multi-output (MIMO) systems. The concept capitalizes on the notion of user statistical separability which was hinted in several prior works in the massive antenna regime but has not fully exploited so far. We propose a hybrid statistical-instantaneous feedback mechanism where the users are separated into two classes of feedback design based on their channel covariance. Under the hybrid framework, each user either operates on a statistical feedback mode or quantized instantaneous channel feedback mode. The key challenge lies in the design of a covariance-aware classification algorithm which can handle the complex mutual interactions among all users. The classification is derived from rate bound principles and a precoding method is also devised under the mixed statistical and instantaneous feedback model. Simulations are performed to validate our analytical results and illustrate the sum rate advantages of the proposed feedback scheme under a global feedback overhead constraint.

A Covariance-Based Hybrid Channel Feedback in FDD Massive MIMO Systems

In this paper, we propose a novel channel feedback scheme for frequency division duplexing massive multi-input multi-output systems. The concept uses the notion of user statistical separability which was hinted in several prior works in the massive antenna regime but not fully exploited so far. We here propose a hybrid statistical-instantaneous feedback scheme based on a user classification mechanism where the classification metric derives from a rate bound analysis. According to classification results, a user either operates on a statistical or instantaneous feedback mode mode. Our results illustrate the sum rate advantages of our scheme under a global feedback overhead constraint.

Enabling Covariance-Based Feedback in Massive MIMO: A User Classification Approach

This paper considers the problem of efficient feedback design for massive multiple-input multiple-output (MIMO) downlink transmissions in frequency division duplexing (FDD) bands, where some partial channel state information (CSI) can be directly exchanged between users via device-to-device (D2D) communications. Drawing inspiration from classical point-to-point MIMO, where efficient mechanisms are obtained by feeding back directly the precoder, this paper proposes a new approach to bridge the channel feedback and the precoder feedback by the joint design of the feedback and precoding strategy following a team decision framework. Specifically, the users and the base station (BS) minimize a common mean squared error (MSE) metric based on their individual observations on the imperfect global CSI. The solutions are found to take similar forms as the regularized zero-forcing (RZF) precoder, with additional regularizations that capture any level of uncertainty in the exchanged CSI, in case the D2D links are absent or unreliable. Numerical results demonstrate superior performance of the proposed scheme for an arbitrary D2D link quality setup.

Dual-Regularized Feedback and Precoding for D2D-Assisted MIMO Systems

The availability of accurate and, most importantly, shared channel state information at the transmitter (CSIT) is one of the key factors that enable transmitters cooperation in decentralized wireless systems. However, in some cases, channel information may not be easily or perfectly shared among the transmitters, thus limiting their coordination capabilities. In this paper we shed some light on the fundamental limits of networks with cooperating transmitters impaired by a general distributed CSIT assumption. To this end, we consider a state-dependent memory-less multiple-access channel with common message, and with noisy causal CSIT and noisy channel state information at the receiver (CSIR). Perhaps surprisingly, and in contrast to the same setting in absence of common message, we show that distributed precoding based on current CSIT only (namely, a Shannon strategy) achieves the sum-rate capacity of this channel, for every degree of CSIT and CSIR. By focusing on the transmission of a common message only, we then illustrate this result in a practically relevant Gaussian setting.

On the Fundamental Limits of Cooperative Multiple-Access Channels with Distributed CSIT

In this work, we develop an algorithm to construct radio maps that can predict the received signal strength between a UAV-mounted base station and arbitrary ground users. The novelty of the work lies in the fact that these maps are constructed by fusing UAV-user radio signal strength measurements, and depth information of the surrounding environment which is obtained by an on-board laser range finder sensor. The proposed approach exploits both line-of-sight (LoS) and non-line-of-sight (NLoS) nature of UAV-user channels and depth information to first obtain the 3D map of the city and then later use it to estimate the radio map. Numerical results demonstrate the significant gain brought by the fusion of radio and depth measurements as opposed to a system which only relies on radio measurements.

David Gesbert

Papers

A Covariance-Based Hybrid Channel Feedback in FDD Massive MIMO Systems

Enabling Covariance-Based Feedback in Massive MIMO: A User Classification Approach

Dual-Regularized Feedback and Precoding for D2D-Assisted MIMO Systems

On the Fundamental Limits of Cooperative Multiple-Access Channels with Distributed CSIT

Map Reconstruction in UAV Networks via Fusion of Radio and Depth Measurements