Topic
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.
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24 Apr 2014
TL;DR: The distinct operation and properties of massive MIMO enable practical resource-efficient load-balancing methods with near-optimal performance on the problem of balancing the load across networks with massive M IMO base-stations.
Abstract: Massive MIMO is expected to play a key role in coping with the predicted mobile-data traffic explosion. Indeed, in combination with small cells and TDD operation, it promises large throughputs per unit area with low latency. In this paper we focus on the problem of balancing the load across networks with massive MIMO base-stations (BSs). The need for load balancing arises from variations in the user population density and is more pronounced in small cells due to the large variability in coverage area. We consider methods for load balancing over networks with small and large massive MIMO BSs. As we show, the distinct operation and properties of massive MIMO enable practical resource-efficient load-balancing methods with near-optimal performance.
95 citations
01 Jan 2003
TL;DR: In this article, an accurate and time-efficient technique for frequency synchronization of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems is proposed.
Abstract: The paper proposes an accurate and time-efficient technique for frequency synchronization of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. The technique uses a preamble and is thus especially suitable for burst mode communication. The preamble consists of training sequences simultaneously transmitted from the various transmit antennas. From analysis, it is shown that the accuracy of frequency synchronization is close to the Cramer-Rao lower bound and increases for increasing RMS delay spreads and number of receive antennas. Furthermore, application of the proposed algorithm in MIMO OFDM wireless local-area-network (WLAN) systems leads to a BER that is only slightly higher than that of a perfectly synchronized system, making it highly applicable.
95 citations
08 Dec 2008
TL;DR: The results show that in most scenarios MU-MIMO provides a higher throughput than SU-M IMO also in the measured channels, however, in outdoor scenarios with a line of sight, the capacity drops significantly when the users are close together, due to high correlation at the transmitter side of the channel.
Abstract: In multi-user multiple-input multiple-output (MU-MIMO) systems, spatial multiplexing can be employed to increase the throughput without the need for multiple antennas and expensive signal processing at the user equipments. In theory, MU-MIMO is also more immune to most of propagation limitations plaguing single-user MIMO (SU-MIMO) systems, such as channel rank loss or antenna correlation. However, in this paper we show that this is not always true. We compare the capacity and the correlation of measured MU-MIMO channels for both outdoor and indoor scenarios. The measurement data has been acquired using Eurecompsilas MIMO openair sounder (EMOS). The EMOS can perform real-time MIMO channel measurements synchronously over multiple users. The results show that in most scenarios MU-MIMO provides a higher throughput than SU-MIMO also in the measured channels. However, in outdoor scenarios with a line of sight, the capacity drops significantly when the users are close together, due to high correlation at the transmitter side of the channel. In such a case, the performance of SU-MIMO and MU-MIMO is comparable.
94 citations
01 Jan 2005
TL;DR: The problem of downlink design can be solved efficiently by focusing on an equivalent uplink problem by solving the problem of minimizing the downlink sum MSE under a sum power constraint by jointly optimizing the linear transmitters and receivers.
Abstract: We address the problem of Mean Square Error (MSE) transceiver design for point-to-multipoint transmission in multi-user Multiple-Input-Multiple-Output (MIMO) systems. We solve the problem of minimizing the downlink sum MSE under a sum power constraint by jointly optimizing the linear transmitters and receivers. Our result is based on a "duality" between downlink and uplink MSE regions. It states that downlink and uplink share the same achievable MSE region under a sum power constraint. Thus, the problem of downlink design can be solved efficiently by focusing on an equivalent uplink problem.
94 citations
09 Sep 2007
TL;DR: It is shown via extensive simulation that as the number of antennas increases, the maximum achievable throughput first rises and then flattens out asymptotically under SRP, while it increases "almost" linearly under SMP or SRMP.
Abstract: Use of multiple antennas or MIMO has great potential for enhancing the throughput of multi-hop wireless networks via spatial reuse and/or spatial division multiplexing. In this paper, we characterize and analyze the maximum achievable throughput in multi-hop wireless MIMO networks under three MIMO protocols, spatial reuse only (SRP), spatial multiplexing only (SMP), and spatial reuse & multiplexing (SRMP), each of which enhances throughput via a different way of exploiting the MIMO's potential. We show via extensive simulation that as the number of antennas increases, the maximum achievable throughput first rises and then flattens out asymptotically under SRP, while it increases "almost" linearly under SMP or SRMP. We evaluate the effects of several network parameters on this achievable throughput. We also demonstrate how these results can be used by designers to determine the optimal parameters of multi-hop wireless MIMO networks.
94 citations