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Multi-Cell MIMO Cooperative Networks: A New Look at Interference
- J. Selec. Areas in Commun. (JSAC
, 2010
"... Abstract—This paper presents an overview of the theory and currently known techniques for multi-cell MIMO (multiple input multiple output) cooperation in wireless networks. In dense networks where interference emerges as the key capacitylimiting factor, multi-cell cooperation can dramatically improv ..."
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Abstract—This paper presents an overview of the theory and currently known techniques for multi-cell MIMO (multiple input multiple output) cooperation in wireless networks. In dense networks where interference emerges as the key capacitylimiting factor, multi-cell cooperation can dramatically improve the system performance. Remarkably, such techniques literally exploit inter-cell interference by allowing the user data to be jointly processed by several interfering base stations, thus mimicking the benefits of a large virtual MIMO array. Multicell MIMO cooperation concepts are examined from different perspectives, including an examination of the fundamental information-theoretic limits, a review of the coding and signal processing algorithmic developments, and, going beyond that, consideration of very practical issues related to scalability and system-level integration. A few promising and quite fundamental research avenues are also suggested. Index Terms—Cooperation, MIMO, cellular networks, relays, interference, beamforming, coordination, multi-cell, distributed.
Network mimo with linear zero-forcing beamforming: Large system analysis, impact of channel estimation, and reduced-complexity scheduling,” Information Theory
- IEEE Transactions on
, 2012
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An overview of massive MIMO: Benefits and challenges
- IEEE J. SEL. TOPICS SIGNAL PROCESS
, 2014
"... Massive multiple-input multiple-output (MIMO) wireless communications refers to the idea equipping cellular base stations (BSs) with a very large number of antennas, and has been shown to potentially allow for orders of magnitude improvement in spectral and energy efficiency using relatively simple ..."
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Cited by 12 (4 self)
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Massive multiple-input multiple-output (MIMO) wireless communications refers to the idea equipping cellular base stations (BSs) with a very large number of antennas, and has been shown to potentially allow for orders of magnitude improvement in spectral and energy efficiency using relatively simple (linear) processing. In this paper, we present a comprehensive overview of state-of-the-art research on the topic, which has recently attracted considerable attention. We begin with an information theoretic analysis to illustrate the conjectured advantages of massive MIMO, and then we address implementation issues related to channel estimation, detection and precoding schemes. We particularly focus on the potential impact of pilot contamination caused by the use of non-orthogonal pilot sequences by users in adjacent cells. We also analyze the energy efficiency achieved by massive MIMO systems, and demonstrate how the degrees of freedom provided by massive MIMO systems enable efficient single-carrier transmission. Finally, the challenges and opportunities associated with implementing massive MIMO in future wireless communications systems are discussed.
Resource allocation for constrained backhaul in picocell networks
- in Proceedings of Information Theory and Application Workshop
, 2011
"... Abstract-Cellular network capacity and coverage can be improved by deployment of low power base stations referred to as picocells. Due to the associated deployment cost, a large number of picocells challenges the traditional approach to backhaul, where each cell has a dedicated backhaul link. This ..."
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Cited by 8 (0 self)
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Abstract-Cellular network capacity and coverage can be improved by deployment of low power base stations referred to as picocells. Due to the associated deployment cost, a large number of picocells challenges the traditional approach to backhaul, where each cell has a dedicated backhaul link. This paper considers a more efficient approach, in which the backhaul is provided over a wireless channel shared among picocells. The considered backhaul network consists of multiple connector nodes (CNs) each providing backhaul to a group of picocells. A key problem in this setting is how to efficiently exploit and allocate this limited bandwidth resource among picocells. We consider joint scheduling and power allocation of backhaul transmissions based on limited bandwidth availability. We propose a backhaul scheduling approach based on traffic demands on picocells (i.e., the load of their mobile users), that maximizes the picocell utility. The approach applies to any underlying physical layer transmission scheme. We then investigate the proposed solution for an OFDM system. We first determine optimal power allocation under power and interference constraints for OFDM transmissions from multiple CNs. We then present an algorithm that performs joint scheduling and power allocation for OFDM transmissions in the backhaul channel.
Multi-cell random beamforming: achievable rate and degrees of freedom region
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Large-Scale MIMO versus Network MIMO for Multicell Interference Mitigation
"... Abstract—This paper compares two distinct downlink multi-cell interference mitigation techniques for wireless cellular net-works: large-scale (LS) multiple-input multiple-output (MIMO) and network MIMO. The considered cellular network operates in a time-division duplex (TDD) fashion and includes non ..."
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Cited by 3 (1 self)
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Abstract—This paper compares two distinct downlink multi-cell interference mitigation techniques for wireless cellular net-works: large-scale (LS) multiple-input multiple-output (MIMO) and network MIMO. The considered cellular network operates in a time-division duplex (TDD) fashion and includes non-overlapping cooperating clusters, where each cluster comprises B base-stations (BSs), each equipped with multiple antennas, and schedules multiple single-antenna users. In the LS-MIMO system, each BS is equipped with BM antennas, serving its K scheduled users using zero-forcing (ZF) beamforming, while sacrificing its excess number of spatial degrees of freedom (DoF) using interference coordination to prevent causing interference to the other K (B − 1) users within the cooperating cluster. In the network MIMO system, although each BS is equipped with M antennas, the intra-cluster interference cancellation is enabled by data and channel state information sharing across the cooperating BSs and joint downlink transmission to BK users via ZF beamforming. Accounting for uplink-downlink channel reciprocity provided by TDD and invoking the orthogonality principle of ZF beamforming, respectively, the channel acqui-sition overhead in each cluster and the number of spatial DoF per user are identical in both systems. Therefore, it is not obvious whether one system is superior to the other from the performance point of view. Building upon the channel distribution functions in the two systems and adopting tools from stochastic orders, this paper shows that in fact an LS-MIMO system provides considerably better performance than a network MIMO system. Thus, given the likely lower cost of adding excess number of antennas, LS-MIMO could be a preferred multicell coordination approach for interference mitigation. I.
A Deterministic Equivalent for the Analysis of Non-Gaussian Correlated MIMO Multiple Access Channels
, 2011
"... Large dimensional random matrix theory (RMT) has provided an efficient analytical tool to understand multiple-input multiple-output (MIMO) channels and to aid the design of MIMO wireless commu-nication systems. However, previous studies based on large dimensional RMT rely on the assumption that the ..."
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Cited by 1 (0 self)
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Large dimensional random matrix theory (RMT) has provided an efficient analytical tool to understand multiple-input multiple-output (MIMO) channels and to aid the design of MIMO wireless commu-nication systems. However, previous studies based on large dimensional RMT rely on the assumption that the transmit correlation matrix is diagonal or the propagation channel matrix is Gaussian. There is an increasing interest in the channels where the transmit correlation matrices are generally nonnegative definite and the channel entries are non-Gaussian. This class of channel models appears in several applications in MIMO multiple access systems, such as small cell networks (SCNs). To address these problems, we use the generalized Lindeberg principle to show that the Stieltjes transforms of this class of random matrices with Gaussian or non-Gaussian independent entries coincide in the large dimensional regime. This result permits to derive the deterministic equivalents (e.g., the Stieltjes transform and the ergodic mutual information) for non-Gaussian MIMO channels from the known results developed for Gaussian MIMO channels, and is of great importance in characterizing the spectral efficiency of SCNs.
Adaptive Beamforming with Per-Antenna Feedback for Multi-Cell Cooperative Networks
"... Beamforming is a signal processing technique that enables antenna arrays to create directional signals, increasing transmitter or receiver gain. We propose a new adaptive user antenna beamforming technique for Multi-cell Cooperative Networks which simultaneously communicates with multiple available ..."
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Beamforming is a signal processing technique that enables antenna arrays to create directional signals, increasing transmitter or receiver gain. We propose a new adaptive user antenna beamforming technique for Multi-cell Cooperative Networks which simultaneously communicates with multiple available BSs and RSs using the MS’s multiple antennas. We show that the proposed adaptive beamforming technique outperforms distributed beamforming by increasing the data rate with less degradation of the BER.
1Dynamic Channel Acquisition in MU-MIMO
"... MIMO) systems are known to be hindered by dimensionality loss due to channel state information (CSI) acquisition overhead. In this paper, we investigate user-scheduling in MU-MIMO systems on account of CSI acquisition overhead, where a base station dynamically acquires user channels to avoid choking ..."
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MIMO) systems are known to be hindered by dimensionality loss due to channel state information (CSI) acquisition overhead. In this paper, we investigate user-scheduling in MU-MIMO systems on account of CSI acquisition overhead, where a base station dynamically acquires user channels to avoid choking the system with CSI overhead. The genie-aided optimization problem (GAP) is first formulated to maximize the Lyapunov-drift every scheduling step, incorporating user queue information and taking channel fluctuations into consideration. The scheduling scheme based on GAP, namely the GAP-rule, is proved to be throughput-optimal but practically infeasible, and thus serves as a performance bound. In view of the implementation overhead and delay unfairness of the GAP-rule, the T-frame dynamic channel acquisition scheme and the power-law DCA scheme are further proposed to mitigate the implementation overhead and delay unfairness, respectively. Both schemes are based on the GAP-rule and proved throughput-optimal. To make the schemes practically feasible, we then propose the heuristic schemes, queue-based quantized-block-length user scheduling scheme (QQS), T-frame QQS, and power-law QQS, which are the practical versions of the aforementioned GAP-based schemes, respectively. The QQS-based schemes substantially decrease the complexity, and also perform fairly close to the optimum. Numerical results evaluate the proposed schemes under various system parameters.
