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Open AccessJournal ArticleDOI

Performance Analysis and Location Optimization for Massive MIMO Systems With Circularly Distributed Antennas

TLDR
In this article, the authors derived an analytical expression for the asymptotic ergodic achievable rate of a single-cell multi-user distributed massive MIMO system under zero-forcing (ZF) detector.
Abstract
We analyze the achievable rate of the uplink of a single-cell multi-user distributed massive multiple-input–multiple-output (MIMO) system. Each user is equipped with single antenna and the base station (BS) is equipped with a large number of distributed antennas. We derive an analytical expression for the asymptotic ergodic achievable rate of the system under zero-forcing (ZF) detector. In particular, we consider circular antenna array, where the distributed BS antennas are located evenly on a circle, and derive an analytical expression and closed-form bounds for the achievable rate of an arbitrarily located user. Subsequently, closed-form bounds on the average achievable rate per user are obtained under the assumption that the users are uniformly located. Based on the bounds, we can understand the behavior of the system rate with respect to different parameters and find the optimal location of the circular BS antenna array that maximizes the average rate. Numerical results are provided to assess our analytical results and examine the impact of the number and the location of the BS antennas, the transmit power, and the path-loss exponent on system performance. Simulations on multi-cell networks are also demonstrated. Our work shows that circularly distributed massive MIMO system largely outperforms centralized massive MIMO system.

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Citations
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Book

Fundamentals of Massive MIMO

TL;DR: This is the first complete guide to the physical and engineering principles of Massive MIMO and will guide readers through key topics in multi-cell systems such as propagation modeling, multiplexing and de-multiplexing, channel estimation, power control, and performance evaluation.
Journal ArticleDOI

A Unified Transmission Strategy for TDD/FDD Massive MIMO Systems With Spatial Basis Expansion Model

TL;DR: A spatial basis expansion model (SBEM) is built to represent the UL/DL channels with far fewer parameter dimensions, which significantly reduces the training overhead and feedback cost and enhances the spectral efficiency.
Journal ArticleDOI

IoT Connectivity Technologies and Applications: A Survey

TL;DR: In this paper, the authors provide a broad view of the existing wireless IoT connectivity technologies and discuss several new emerging technologies and solutions that can be effectively used to enable massive connectivity for IoT.
Journal ArticleDOI

An Overview of Enhanced Massive MIMO With Array Signal Processing Techniques

TL;DR: In this paper, the authors present an overview of recent progress on merging array signal processing into massive MIMO communications as well as its promising future directions, and some phenomena of the beam squint effect can be better explained now with array signals processing.
Journal ArticleDOI

Spectral-Efficiency Analysis of Massive MIMO Systems in Centralized and Distributed Schemes

TL;DR: It is attested that for the D-MIMO of cell radius rc and circular antenna array of radius ra, the optimal value of ra that maximizes the average spectral efficiency is accurately established by raopt = rc/1.31.
References
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Book

Table of Integrals, Series, and Products

TL;DR: Combinations involving trigonometric and hyperbolic functions and power 5 Indefinite Integrals of Special Functions 6 Definite Integral Integral Functions 7.Associated Legendre Functions 8 Special Functions 9 Hypergeometric Functions 10 Vector Field Theory 11 Algebraic Inequalities 12 Integral Inequality 13 Matrices and related results 14 Determinants 15 Norms 16 Ordinary differential equations 17 Fourier, Laplace, and Mellin Transforms 18 The z-transform
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Capacity of Multi‐antenna Gaussian Channels

TL;DR: In this paper, the authors investigate the use of multiple transmitting and/or receiving antennas for single user communications over the additive Gaussian channel with and without fading, and derive formulas for the capacities and error exponents of such channels, and describe computational procedures to evaluate such formulas.
Book

Fundamentals of Wireless Communication

TL;DR: In this paper, the authors propose a multiuser communication architecture for point-to-point wireless networks with additive Gaussian noise detection and estimation in the context of MIMO networks.
Journal ArticleDOI

Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas

TL;DR: A cellular base station serves a multiplicity of single-antenna terminals over the same time-frequency interval and a complete multi-cellular analysis yields a number of mathematically exact conclusions and points to a desirable direction towards which cellular wireless could evolve.
Journal ArticleDOI

Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays

TL;DR: The gains in multiuser systems are even more impressive, because such systems offer the possibility to transmit simultaneously to several users and the flexibility to select what users to schedule for reception at any given point in time.
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