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Journal ArticleDOI

Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas

Thomas L. Marzetta1
01 Nov 2010-IEEE Transactions on Wireless Communications (IEEE)-Vol. 9, Iss: 11, pp 3590-3600
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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Journal ArticleDOI
TL;DR: In this paper, the authors propose a maximum likelihood solution to determine the unknown position of a mobile station for a mmWave MISO system. But the problem is not solved in the downlink, where the time of flight and angle of departure of received downlink signals are considered.
Abstract: This paper addresses the problem of determining the unknown position of a mobile station for a mmWave multiple-input single-output (MISO) system. This setup is motivated by the fact that massive arrays will be initially implemented only on 5G base stations, likely leaving mobile stations with one antenna. The maximum likelihood solution to this problem is devised based on the time of flight and angle of departure of received downlink signals. While positioning in the uplink would rely on angle of arrival, it presents scalability limitations that are avoided in the downlink. To circumvent the multidimensional optimization of the optimal joint estimator, we propose two novel approaches amenable to practical implementation thanks to their reduced complexity. A thorough analysis, which includes the derivation of relevant Cramer–Rao lower bounds, shows that it is possible to achieve quasi-optimal performance even in presence of few transmissions, low signal-to-noise ratio (SNRs), and multipath propagation effects.

72 citations

Journal ArticleDOI
TL;DR: A robust Wald-type test is developed that implies that there always exists a sufficient number of antennas for which the performance requirements are satisfied, without any a-priori knowledge of the disturbance statistics.
Abstract: Since the seminal paper by Marzetta from 2010, the Massive MIMO paradigm in communication systems has changed from being a theoretical scaled-up version of MIMO, with an infinite number of antennas, to a practical technology. Its key concepts have been adopted in the 5G new radio standard and base stations, where 64 fully-digital transceivers have been commercially deployed. Motivated by these recent developments, this paper considers a co-located MIMO radar with $M_T$ transmitting and $M_R$ receiving antennas and explores the potential benefits of having a large number of virtual spatial antenna channels $N=M_TM_R$ . Particularly, we focus on the target detection problem and develop a robust Wald-type test that guarantees certain detection performance, regardless of the unknown statistical characterization of the disturbance. Closed-form expressions for the probabilities of false alarm and detection are derived for the asymptotic regime $N\rightarrow \infty$ . Numerical results are used to validate the asymptotic analysis in the finite system regime with different disturbance models. Our results imply that there always exists a sufficient number of antennas for which the performance requirements are satisfied, without any a-priori knowledge of the disturbance statistics. This is referred to as the Massive MIMO regime of the radar system.

72 citations


Cites methods from "Noncooperative Cellular Wireless wi..."

  • ...Inspired by the recent developments in Massive MIMO communications [7]–[10], we aim at exploring the potential benefits of having a very large number of antennas....

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Journal ArticleDOI
TL;DR: 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.

72 citations

Proceedings ArticleDOI
01 Sep 2013
TL;DR: In this paper, energy efficient power allocation scheme is investigated for the massive MIMO system with the maximum ratio transmission (MRT) precoding, since MRT precoding can balance the system performance and complexity.
Abstract: Massive multiple-input multiple-output (MIMO) has been seen as a promising technology to improve the spectrum efficiency (SE), reliability and energy efficiency (EE) for the next generation wireless communication systems. Excessive energy consumption of wireless communication networks induces both the increasing carbon emission and unaffordable operational expenditure in recent years. In this paper, energy efficient power allocation scheme is investigated for the massive MIMO system with the maximum ratio transmission (MRT) precoding, since MRT precoding can balance the system performance and complexity. As of the intractable expression of the received SINR at user terminal (UT), an approximate expression is deduced by proper simplification. Based on the simplified expression, a power allocation algorithm is proposed to achieve the optimal EE according to convex optimization theory. Compared with the power allocation scheme ignoring the inter user interference, the proposed power allocation algorithm can enhance EE and decrease transmission power, and does not impair the SE. Simulation results also show that both the EE and SE are improved by increasing the number of antennas at BS and the number of multiple UTs.

72 citations


Cites background or methods from "Noncooperative Cellular Wireless wi..."

  • ...The mainly research fields are as follows [3] [4]: design of massive antennas array, measure and modeling of massive MIMO channel, performance analysis of the massive MIMO system, precoding mechanisms for transmitter, channel estimation and detection at receiver, interference controlling and resource scheduling algorithm, etc....

    [...]

  • ...During past years, multiple-input multipleoutput (MIMO) has been researched widely and applied to LTE or LTE-Advanced [2]; Recently, massive MIMO has been put forward to improve spectrum efficiency (SE), reliability and energy efficiency (EE) by installing massive antennas at the existing BS, which is promising for the next wireless communication systems [3]....

    [...]

Proceedings ArticleDOI
Xinyu Gao1, Linglong Dai1, Yuting Hu1, Zhongxu Wang1, Zhaocheng Wang1 
01 Dec 2014
TL;DR: A low-complexity signal detection algorithm based on the successive overrelaxation (SOR) method to avoid the complicated matrix inversion for uplink large-scale MIMO systems is proposed.
Abstract: For uplink large-scale MIMO systems, linear minimum mean square error (MMSE) signal detection algorithm is near-optimal but involves matrix inversion with high complexity. In this paper, we propose a low-complexity signal detection algorithm based on the successive overrelaxation (SOR) method to avoid the complicated matrix inversion. We first prove a special property that the MMSE filtering matrix is symmetric positive definite for uplink large-scale MIMO systems, which is the premise for the SOR method. Then a low-complexity iterative signal detection algorithm based on the SOR method as well as the convergence proof is proposed. The analysis shows that the proposed scheme can reduce the computational complexity from O(K3) to O(K2), where K is the number of users. Finally, we verify through simulation results that the proposed algorithm outperforms the recently proposed Neumann series approximation algorithm, and achieves the near-optimal performance of the classical MMSE algorithm with a small number of iterations.

72 citations


Cites background or methods from "Noncooperative Cellular Wireless wi..."

  • ..., 128 antennas or even more) at the base station (BS) to simultaneously serve multiple user equipments (UEs) [2]....

    [...]

  • ...Unlike the traditional small-scale MIMO technology (e.g., at most 8 antennas in LTE-A), large-scale MIMO exploits a very large number of antennas (e.g., 128 antennas or even more) at the base station (BS) to simultaneously serve multiple user equipments (UEs) [2]....

    [...]

  • ...We consider a uplink large-scale MIMO system employing N antennas at the BS to simultaneously serve K singleantenna UEs [2], [4]....

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  • ...) with z ero mean and unit variance [2]....

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  • ...SYSTEM MODEL We consider a uplink large-scale MIMO system employing N antennas at the BS to simultaneously serveK singleantenna UEs [2], [4]....

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References
More filters
Journal ArticleDOI
Gerard J. Foschini1
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....

    [...]

Journal ArticleDOI
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....

    [...]

Book
28 Jun 2004
TL;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]....

    [...]

Journal ArticleDOI
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....

    [...]