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Multi-user MIMO

About: Multi-user MIMO is a research topic. Over the lifetime, 10265 publications have been published within this topic receiving 227206 citations. The topic is also known as: multi user mimo & MU-MIMO.


Papers
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Proceedings ArticleDOI
01 Dec 2014
TL;DR: This work investigates the properties of measured Massive MIMO channels in a large indoor venue and finds that performance is improved as the aperture increases, with an impact mostly visible in crowded scenarios where the users are closely spaced.
Abstract: Massive MIMO is a new technique for wireless communications that claims to offer very high system throughput and energy efficiency in multi-user scenarios. The cost is to add a very large number of antennas at the base station. Theoretical research has probed these benefits, but very few measurements have showed the potential of Massive MIMO in practice. We investigate the properties of measured Massive MIMO channels in a large indoor venue. We describe a measurement campaign using 3 arrays having different shape and aperture, with 64 antennas and 8 users with 2 antennas each. We focus on the impact of the array aperture which is the main limiting factor in the degrees of freedom available in the multiple antenna channel. We find that performance is improved as the aperture increases, with an impact mostly visible in crowded scenarios where the users are closely spaced. We also test MIMO capability within a same user device with user proximity effect. We see a good channel resolvability with confirmation of the strong effect of the user hand grip. At last, we highlight that propagation conditions where line-of-sight is dominant can be favourable.

104 citations

Armin Wittneben, B. Rankov1
01 Jan 2006
TL;DR: The results show that the proposed cooperative signaling scheme solves a fundamental problem of MIMO systems: the rich scattering requirement.
Abstract: We study the impact of multiple linear amplifyand-forward relays on the capacity of rank-deficient MIMO channels. We derive a general system model for wireless networks with one source/destination pair and several linear amplify-and-forward relay nodes which assist the communication between source and destination. All nodes may be equipped with multiple antennas. For a given allocation of gain factors at the relay nodes we give an analytical expression of the capacity by generalizing the results in [1], [2]. We compare the performance of a relay assisted MIMO link in a line-of-sight environment with a MIMO link without relay nodes. Our results show that the proposed cooperative signaling scheme solves a fundamental problem of MIMO systems: the rich scattering requirement.

104 citations

Journal ArticleDOI
TL;DR: This paper proposes a novel decentralized baseband processing architecture that alleviates bottlenecks by partitioning the BS antenna array into clusters, each associated with independent radio-frequency chains, analog and digital modulation circuitry, and computing hardware.
Abstract: Achieving high spectral efficiency in realistic massive multi-user (MU) multiple-input multiple-output (MIMO) wireless systems requires computationally complex algorithms for data detection in the uplink (users transmit to base-station) and beamforming in the downlink (base-station transmits to user). Most existing algorithms are designed to be executed on centralized computing hardware at the base-station (BS), which results in prohibitive complexity for systems with hundreds or thousands of antennas and generates raw baseband data rates that exceed the limits of current interconnect technology and chip I/O interfaces. This paper proposes a novel decentralized baseband processing architecture that alleviates these bottlenecks by partitioning the BS antenna array into clusters, each associated with independent radio-frequency chains, analog and digital modulation circuitry, and computing hardware. For this architecture, we develop novel decentralized data detection and beamforming algorithms that only access local channel-state information and require low communication bandwidth among the clusters. We study the associated tradeoffs between error-rate performance, computational complexity, and interconnect bandwidth, and we demonstrate the scalability of our solutions for massive MU-MIMO systems with thousands of BS antennas using reference implementations on a graphics processing unit (GPU) cluster.

104 citations

Proceedings ArticleDOI
01 Dec 2014
TL;DR: The effects of hardware impairments on a massive MU-MIMO single-cell system is examined by means of theory and simulation using simplified, well-established statistical hardware impairment models as well as more sophisticated and realistic models based upon measurements and electromagnetic antenna array simulations.
Abstract: Massive multi-user (MU) multiple-input multiple-output (MIMO) systems are one possible key technology for next generation wireless communication systems. Claims have been made that massive MU-MIMO will increase both the radiated energy efficiency as well as the sum-rate capacity by orders of magnitude, because of the high transmit directivity. However, due to the very large number of transceivers needed at each base-station (BS), a successful implementation of massive MU-MIMO will be contingent on of the availability of very cheap, compact and power-efficient radio and digital-processing hardware. This may in turn impair the quality of the modulated radio frequency (RF) signal due to an increased amount of power-amplifier distortion, phase-noise, and quantization noise. In this paper, we examine the effects of hardware impairments on a massive MU-MIMO single-cell system by means of theory and simulation. The simulations are performed using simplified, well-established statistical hardware impairment models as well as more sophisticated and realistic models based upon measurements and electromagnetic antenna array simulations.

103 citations

Journal ArticleDOI
TL;DR: This work proposes a downlink antenna selection scheme, which selects S antennas from M > S transmit antennas based on the large scale fading to serve K ≤ S users in large distributed MIMO networks employing regularized zero-forcing (RZF) precoding.
Abstract: Large multiple-input multiple-output (MIMO) networks promise high energy efficiency, i.e., much less power is required to achieve the same capacity compared to the conventional MIMO networks if perfect channel state information (CSI) is available at the transmitter. However, in such networks, huge overhead is required to obtain full CSI especially for Frequency-Division Duplex (FDD) systems. To reduce overhead, we propose a downlink antenna selection scheme, which selects S antennas from M > S transmit antennas based on the large scale fading to serve K ≤ S users in large distributed MIMO networks employing regularized zero-forcing (RZF) precoding. In particular, we study the joint optimization of antenna selection, regularization factor, and power allocation to maximize the average weighted sum-rate. This is a mixed combinatorial and non-convex problem whose objective and constraints have no closed-form expressions. We apply random matrix theory to derive asymptotically accurate expressions for the objective and constraints. As such, the joint optimization problem is decomposed into subproblems, each of which is solved by an efficient algorithm. In addition, we derive structural solutions for some special cases and show that the capacity of very large distributed MIMO networks scales as O(KlogM) when M→∞ with K, S fixed. Simulations show that the proposed scheme achieves significant performance gain over various baselines.

103 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202363
2022122
2021170
2020211
2019234
2018263