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.
Abstract: 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.
Citations
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TL;DR: In this paper, a low-complexity Gaussian message passing iterative detection (GMPID) algorithm for a massive multiuser multiple-input multiple-output (MU-MIMO) system, in which a base station with $M$ antennas serves $K$ Gaussian sources simultaneously, is considered.
Abstract: This paper considers a low-complexity Gaussian message passing iterative detection (GMPID) algorithm for a massive multiuser multiple-input multiple-output (MU-MIMO) system, in which a base station with $M$ antennas serves $K$ Gaussian sources simultaneously. Both $K$ and $M$ are very large numbers, and we consider the cases that $K . The GMPID is a message passing algorithm operating on a fully connected loopy graph, which is well understood to be non-convergent in some cases. As it is hard to analyze the GMPID directly, the large-scale property of the massive MU-MIMO is used to simplify the analysis. First, we prove that the variances of the GMPID definitely converge to the mean square error of minimum mean square error (mmse) detection. Second, we derive two sufficient conditions that make the means of the GMPID converge to those of the mmse detection. However, the means of GMPID may not converge when $ K/M\geq (\sqrt {2}-1)^{2}$ . Therefore, a modified GMPID called scale-and-add GMPID, which converges to the mmse detection in mean and variance for any $K , and has a faster convergence speed than the GMPID, but has no higher complexity than the GMPID, is proposed. Finally, numerical results are provided to verify the validity and accuracy of the theoretical results.
96 citations
TL;DR: The effects of the ratio of thenumber of massive MIMO antennas to the number of users on the performance of NS-based MIA is analyzed and the approximation error estimation formulas for different practical numbers of terms of NS -based MIA are derived.
Abstract: Zero-Forcing (ZF) has been considered as one of the potential practical precoding and detection method for massive MIMO systems. One of the most important advantages of massive MIMO is the capability of supporting a large number of users in the same time-frequency resource, which requires much larger dimensions of matrix inversion for ZF than conventional multi-user MIMO systems. In this case, Neumann Series (NS) has been considered for the Matrix Inversion Approximation (MIA), because of its suitability for massive MIMO systems and its advantages in hardware implementation. The performance-complexity trade-off and the hardware implementation of NS-based MIA in massive MIMO systems have been discussed. In this paper, we analyze the effects of the ratio of the number of massive MIMO antennas to the number of users on the performance of NS-based MIA. In addition, we derive the approximation error estimation formulas for different practical numbers of terms of NS-based MIA. These results could offer useful guidelines for practical massive MIMO systems.
96 citations
Cites background from "Noncooperative Cellular Wireless wi..."
...Therefore, they can achieve significantly higher spatial multiplexing gains than conventional multi-user MIMO systems, which offers one of the most important advantages of massive MIMO systems, the potential capability to offer linear capacity growth without increasing power or bandwidth [1]–[4]....
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...Note that, for the Time-Division Duplexing (TDD) mode, due to the channel reciprocity, the downlink has the same channel matrix H as the uplink, as long as the transmission duration is within the channel coherence time [1]–[6]....
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...zero-mean unit-variance complex Gaussian random variables, when the number ofM is large, the diagonal elements of D approach to ME{|hkk|(2)} = M by the law of large numbers [1], [2], [4]....
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...INTRODUCTION Massive Multiple-Input Multiple-Output (MIMO) systems were firstly introduced in [1], and have drawn great interest form both academia and industry....
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Posted Content•
01 Jan 2016TL;DR: In this article, the authors proposed a joint spatial division and multiplexing (JSDM) scheme where the downlink precoder is split into the product of a baseband linear projection (digital) and an RF reconfigurable beamforming network (analog).
Abstract: Massive MIMO is a variant of multiuser MIMO where the number of base-station antennas M is very large (typically ≈ 100), and generally much larger than the number of spatially multiplexed data streams (typically ≈ 10). The benefits of such approach have been intensively investigated in the past few years, and all-digital experimental implementations have also been demonstrated. Unfortunately, the front-end A/D conversion necessary to drive hundreds of antennas, with a signal bandwidth of the order of 10 to 100 MHz, requires very large sampling bitrate and power consumption. In order to reduce such implementation requirements, Hybrid Digital-Analog architectures have been proposed. In particular, our work in this paper is motivated by one of such schemes named Joint Spatial Division and Multiplexing (JSDM), where the downlink precoder (resp., uplink linear receiver) is split into the product of a baseband linear projection (digital) and an RF reconfigurable beamforming network (analog), such that only a reduced number m M of A/D converters and RF modulation/demodulation chains is needed. In JSDM, users are grouped according to similarity of their channel dominant subspaces, and these groups are separated by the analog beamforming stage, where multiplexing gain in each group is achieved using the digital precoder. Therefore, it is apparent that extracting the channel subspace information of the M -dim channel vectors from snapshots of m-dim projections, with m M , plays a fundamental role in JSDM implementation. In this paper, we develop novel efficient algorithms that require sampling only m = O(2 √ M) specific array elements according to a coprime sampling scheme, and for a given p M , return a p-dim beamformer that has a performance comparable with the best p-dim beamformer that can be designed from the full knowledge of the exact channel covariance matrix. We assess the performance of our proposed estimators both analytically and empirically via numerical simulations. We also demonstrate by simulation that the proposed subspace estimation methods provide near-ideal performance for a massive MIMO JSDM system, by comparing with the case where the user channel covariances are perfectly known.
96 citations
TL;DR: Field measurements from 32 to 256 antenna elements at the transmitter and 16 antenna element at the receiver are performed in three typical deployment scenarios, including outdoor to indoor, urban microcell, and urban macrocell at both 3.5 and 6 GHz frequencies with 200 MHz bandwidth to gain insights into the 3D massive MIMO channel and performance.
Abstract: By placing active antennas in a 2D grid at a BS, 3D MIMO is considered as a promising and practical technique for 5G New Radio (NR). So far, 3D MIMO studies reported are mostly done with antenna elements from 32 up to 128 in the limited scenario at one frequency. To gain further insights into the 3D massive MIMO channel and performance, field measurements from 32 to 256 antenna elements at the transmitter and 16 antenna elements at the receiver are performed in three typical deployment scenarios, including outdoor to indoor, urban microcell, and urban macrocell at both 3.5 and 6 GHz frequencies with 200 MHz bandwidth. Based on the extracted channel information from measured data, power angle spectrum, root mean square angle spread, channel capacity, and eigenvalue spread have been studied. Several observations, including 3D MIMO channel spatial dispersive properties and multi-user performance varying with antenna number, scenario, and frequency are given. These findings can provide valuable experimental insights for efficient utilization of 3D MIMO with massive antenna elements.
96 citations
30 Sep 2013
TL;DR: ArgosV2 is intended to provide ultimate scalability and programmability for experimental massive-MIMO research, and will unveil a 96-antenna base station which supports real-time streaming applications to 32 users simultaneously.
Abstract: Many-antenna base stations are a rapidly growing field in wireless research. A plethora of new theoretical techniques have been recently proposed for many-antenna base stations and networks. However, without experimental validation, it is difficult or impossible to predict the practicality and performance of these techniques in real hardware, under complex, rapidly varying, real-world conditions. Indeed, there is a significant demand for a flexible many-antenna research platform which supports rapid prototyping and validation of new massive-MIMO techniques. Leveraging our experience building Argos, a 64-antenna base station prototype, we have designed and built ArgosV2, a compact, powerful, and scalable many-antenna research platform based on WARP. In addition to the physical hardware and mechanical design, we are developing a software framework, ArgosLab, which will provide synchronization and channel estimation, greatly reducing the development effort for a wide range of massive-MIMO techniques. ArgosV2 is intended to provide ultimate scalability and programmability for experimental massive-MIMO research. The modular architecture and real-time capability of ArgosV2 can support up to 100s of base station antennas and 10s of users with streaming applications. For our demonstration, we will unveil a 96-antenna base station which supports real-time streaming applications to 32 users simultaneously.
96 citations
Cites methods from "Noncooperative Cellular Wireless wi..."
...Over the past few years, there has been a plethora of new massive-MIMO techniques proposed, such as [2, 3, 4, 5], and many more....
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References
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TL;DR: This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver with the aim of leveraging the already highly developed 1-D codec technology.
Abstract: This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver. Inventing a codec architecture that can realize a significant portion of the great capacity promised by information theory is essential to a standout long-term position in highly competitive arenas like fixed and indoor wireless. Use (n T , n R ) to express the number of antenna elements at the transmitter and receiver. An (n, n) analysis shows that despite the n received waves interfering randomly, capacity grows linearly with n and is enormous. With n = 8 at 1% outage and 21-dB average SNR at each receiving element, 42 b/s/Hz is achieved. The capacity is more than 40 times that of a (1, 1) system at the same total radiated transmitter power and bandwidth. Moreover, in some applications, n could be much larger than 8. In striving for significant fractions of such huge capacities, the question arises: Can one construct an (n, n) system whose capacity scales linearly with n, using as building blocks n separately coded one-dimensional (1-D) subsystems of equal capacity? With the aim of leveraging the already highly developed 1-D codec technology, this paper reports just such an invention. In this new architecture, signals are layered in space and time as suggested by a tight capacity bound.
6,812 citations
"Noncooperative Cellular Wireless wi..." refers background in this paper
...A point-to-point MIMO system [2] requires expensive multiple-antenna terminals....
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TL;DR: Under certain mild conditions, this scheme is found to be throughput-wise asymptotically optimal for both high and low signal-to-noise ratio (SNR), and some numerical results are provided for the ergodic throughput of the simplified zero-forcing scheme in independent Rayleigh fading.
Abstract: A Gaussian broadcast channel (GBC) with r single-antenna receivers and t antennas at the transmitter is considered. Both transmitter and receivers have perfect knowledge of the channel. Despite its apparent simplicity, this model is, in general, a nondegraded broadcast channel (BC), for which the capacity region is not fully known. For the two-user case, we find a special case of Marton's (1979) region that achieves optimal sum-rate (throughput). In brief, the transmitter decomposes the channel into two interference channels, where interference is caused by the other user signal. Users are successively encoded, such that encoding of the second user is based on the noncausal knowledge of the interference caused by the first user. The crosstalk parameters are optimized such that the overall throughput is maximum and, surprisingly, this is shown to be optimal over all possible strategies (not only with respect to Marton's achievable region). For the case of r>2 users, we find a somewhat simpler choice of Marton's region based on ordering and successively encoding the users. For each user i in the given ordering, the interference caused by users j>i is eliminated by zero forcing at the transmitter, while interference caused by users j
2,616 citations
"Noncooperative Cellular Wireless wi..." refers background in this paper
...An alternative to a point-to-point MIMO system is a multiuser MIMO system [3], [4], [5], [6] in which an antenna array simultaneously serves a multiplicity of autonomous terminals....
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Book•
28 Jun 2004TL;DR: A tutorial on random matrices is provided which provides an overview of the theory and brings together in one source the most significant results recently obtained.
Abstract: Random matrix theory has found many applications in physics, statistics and engineering since its inception. Although early developments were motivated by practical experimental problems, random matrices are now used in fields as diverse as Riemann hypothesis, stochastic differential equations, condensed matter physics, statistical physics, chaotic systems, numerical linear algebra, neural networks, multivariate statistics, information theory, signal processing and small-world networks. This article provides a tutorial on random matrices which provides an overview of the theory and brings together in one source the most significant results recently obtained. Furthermore, the application of random matrix theory to the fundamental limits of wireless communication channels is described in depth.
2,308 citations
"Noncooperative Cellular Wireless wi..." refers background in this paper
...It can be shown that the vector φkjΦ ∗ l has exactly the same probability distribution as does any row vector of Φl [15], [16]....
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01 Jan 2004
2,180 citations
TL;DR: It is shown that the dirty paper achievable region achieves the sum-rate capacity of the MIMO BC by establishing that the maximum sum rate of this region equals an upper bound on the sum rate.
Abstract: We consider a multiuser multiple-input multiple- output (MIMO) Gaussian broadcast channel (BC), where the transmitter and receivers have multiple antennas. Since the MIMO BC is in general a nondegraded BC, its capacity region remains an unsolved problem. We establish a duality between what is termed the "dirty paper" achievable region (the Caire-Shamai (see Proc. IEEE Int. Symp. Information Theory, Washington, DC, June 2001, p.322) achievable region) for the MIMO BC and the capacity region of the MIMO multiple-access channel (MAC), which is easy to compute. Using this duality, we greatly reduce the computational complexity required for obtaining the dirty paper achievable region for the MIMO BC. We also show that the dirty paper achievable region achieves the sum-rate capacity of the MIMO BC by establishing that the maximum sum rate of this region equals an upper bound on the sum rate of the MIMO BC.
1,802 citations
"Noncooperative Cellular Wireless wi..." refers background in this paper
...An alternative to a point-to-point MIMO system is a multiuser MIMO system [3], [4], [5], [6] in which an antenna array simultaneously serves a multiplicity of autonomous terminals....
[...]