Results 1  10
of
132
MultiCell 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 multicell MIMO (multiple input multiple output) cooperation in wireless networks. In dense networks where interference emerges as the key capacitylimiting factor, multicell cooperation can dramatically improv ..."
Abstract

Cited by 250 (39 self)
 Add to MetaCart
(Show Context)
Abstract—This paper presents an overview of the theory and currently known techniques for multicell MIMO (multiple input multiple output) cooperation in wireless networks. In dense networks where interference emerges as the key capacitylimiting factor, multicell cooperation can dramatically improve the system performance. Remarkably, such techniques literally exploit intercell 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 informationtheoretic limits, a review of the coding and signal processing algorithmic developments, and, going beyond that, consideration of very practical issues related to scalability and systemlevel integration. A few promising and quite fundamental research avenues are also suggested. Index Terms—Cooperation, MIMO, cellular networks, relays, interference, beamforming, coordination, multicell, distributed.
Coordinated beamforming for the multicell multiantenna wireless system
 IEEE Trans. Wireless Commun
"... Abstract—In a conventional wireless cellular system, signal processing is performed on a percell basis; outofcell interference is treated as background noise. This paper considers the benefit of coordinating basestations across multiple cells in a multiantenna beamforming system, where multiple ..."
Abstract

Cited by 114 (6 self)
 Add to MetaCart
(Show Context)
Abstract—In a conventional wireless cellular system, signal processing is performed on a percell basis; outofcell interference is treated as background noise. This paper considers the benefit of coordinating basestations across multiple cells in a multiantenna beamforming system, where multiple basestations may jointly optimize their respective beamformers to improve the overall system performance. This paper focuses on a downlink scenario where each remote user is equipped with a single antenna, but where multiple remote users may be active simultaneously in each cell. The design criterion is the minimization of the total weighted transmitted power across the basestations subject to signaltointerferenceandnoiseratio (SINR) constraints at the remote users. The main contribution is a practical algorithm that is capable of finding the joint optimal beamformers for all basestations globally and efficiently. The proposed algorithm is based on a generalization of uplinkdownlink duality to the multicell setting using the Lagrangian duality theory. The algorithm also naturally leads to a distributed implementation. Simulation results show that a coordinated beamforming system can significantly outperform a conventional system with percell signal processing. I.
Networked MIMO with Clustered Linear Precoding
, 2008
"... A clustered base transceiver station (BTS) coordination strategy is proposed for a large cellular MIMO network, which includes full intracluster coordination–to enhance the sum rate–and limited intercluster coordination–to reduce interference for the cluster edge users. Multicell block diagonaliz ..."
Abstract

Cited by 90 (19 self)
 Add to MetaCart
A clustered base transceiver station (BTS) coordination strategy is proposed for a large cellular MIMO network, which includes full intracluster coordination–to enhance the sum rate–and limited intercluster coordination–to reduce interference for the cluster edge users. Multicell block diagonalization is used to coordinate the transmissions across multiple BTSs in the same cluster. To satisfy perBTS power constraints, three combined precoder and power allocation algorithms are proposed with different performance and complexity tradeoffs. For intercluster coordination, the coordination area is chosen to balance fairness for edge users and the achievable sum rate. It is shown that a small cluster size (about 7 cells) is sufficient to obtain most of the sum rate benefits from clustered coordination while greatly relieving channel feedback requirement. Simulations show that the proposed coordination strategy efficiently reduces interference and provides a considerable sum rate gain for cellular MIMO networks.
Weighted SumRate Maximization using Weighted MMSE for MIMOBC Beamforming Design
 IEEE Trans. on Wireless Comm
, 2008
"... Abstract—This paper studies linear transmit filter design for Weighted SumRate (WSR) maximization in the Multiple Input Multiple Output Broadcast Channel (MIMOBC). The problem of finding the optimal transmit filter is nonconvex and intractable to solve using low complexity methods. Motivated by r ..."
Abstract

Cited by 59 (2 self)
 Add to MetaCart
(Show Context)
Abstract—This paper studies linear transmit filter design for Weighted SumRate (WSR) maximization in the Multiple Input Multiple Output Broadcast Channel (MIMOBC). The problem of finding the optimal transmit filter is nonconvex and intractable to solve using low complexity methods. Motivated by recent results highlighting the relationship between mutual information and Minimum Mean Square Error (MMSE), this paper establishes a relationship between weighted sumrate and weighted MMSE in the MIMOBC. The relationship is used to propose two low complexity algorithms for finding a local weighted sumrate optimum based on alternating optimization. Numerical results studying sumrate show that the proposed algorithms achieve high performance with few iterations. Index Terms—MIMO systems, transceiver design, smart antennas, antennas and propagation. I.
An introduction to convex optimization for communications and signal processing
 IEEE J. Sel. Areas Commun
, 2006
"... Abstract—Convex optimization methods are widely used in the ..."
Abstract

Cited by 55 (2 self)
 Add to MetaCart
(Show Context)
Abstract—Convex optimization methods are widely used in the
Zero Forcing Precoding and Generalized Inverses
"... We consider the problem of linear zero forcing precoding design, and discuss its relation to the theory of generalized inverses in linear algebra. Special attention is given to a specific generalized inverse known as the pseudoinverse. We begin with the standard design under the assumption of a tot ..."
Abstract

Cited by 53 (0 self)
 Add to MetaCart
(Show Context)
We consider the problem of linear zero forcing precoding design, and discuss its relation to the theory of generalized inverses in linear algebra. Special attention is given to a specific generalized inverse known as the pseudoinverse. We begin with the standard design under the assumption of a total power constraint and prove that precoders based on the pseudoinverse are optimal in this setting. Then, we proceed to examine individual perantenna power constraints. In this case, the pseudoinverse is not necessarily the optimal generalized inverse. In fact, finding the optimal inverse is nontrivial and depends on the specific performance measure. We address two common criteria, fairness and throughput, and show that the optimal matrices may be found using standard convex optimization methods. We demonstrate the improved performance offered by our approach using computer simulations.
Dynamic resource allocation in cognitive radio networks
 IEEE Signal Process. Mag
, 2010
"... ar ..."
(Show Context)
Optimal resource allocation for MIMO ad hoc cognitive radio networks
 in Proc. 46th Annu. Allerton Conf. Commun., Control, Comput
, 2008
"... Abstract—Maximization of the weighted sumrate of secondary users (SUs) possibly equipped with multiantenna transmitters and receivers is considered in the context of cognitive radio (CR) networks with coexisting primary users (PUs). The total interference power received at the primary receiver is ..."
Abstract

Cited by 39 (0 self)
 Add to MetaCart
(Show Context)
Abstract—Maximization of the weighted sumrate of secondary users (SUs) possibly equipped with multiantenna transmitters and receivers is considered in the context of cognitive radio (CR) networks with coexisting primary users (PUs). The total interference power received at the primary receiver is constrained to maintain reliable communication for the PU. An interference channel configuration is considered for ad hoc networking, where the receivers treat the interference from undesired transmitters as noise. Without the CR constraint, a convergent distributed algorithm is developed to obtain (at least) a locally optimal solution. With the CR constraint, a semidistributed algorithm is introduced. An alternative centralized algorithm based on geometric programming and network duality is also developed. Numerical results show the efficacy of the proposed algorithms. The novel approach is flexible to accommodate modifications aiming at interference alignment. However, the standalone weighted sumrate optimal schemes proposed here have merits over interferencealignment alternatives especially for practical SNR values. Index Terms—Ad hoc network, cognitive radio, interference network, MIMO, optimization. I.
Linear precoding in cooperative MIMO cellular networks with limited coordination clusters
 IEEE J. Sel. Areas Commun
, 2010
"... ar ..."
(Show Context)
1 Adaptive Spatial Intercell Interference Cancellation in Multicell Wireless Networks
, 909
"... Downlink spatial intercell interference cancellation (ICIC) is considered for mitigating othercell interference using multiple transmit antennas. A principle question we explore is whether it is better to do ICIC or simply standard singlecell beamforming. We explore this question analytically and ..."
Abstract

Cited by 30 (8 self)
 Add to MetaCart
(Show Context)
Downlink spatial intercell interference cancellation (ICIC) is considered for mitigating othercell interference using multiple transmit antennas. A principle question we explore is whether it is better to do ICIC or simply standard singlecell beamforming. We explore this question analytically and show that beamforming is preferred for all users when the edge SNR (signaltonoise ratio) is low (< 0 dB), and ICIC is preferred when the edge SNR is high (> 10 dB), for example in an urban setting. At medium SNR, a proposed adaptive strategy, where multiple base stations jointly select transmission strategies based on the user location, outperforms both while requiring a lower feedback rate than the pure ICIC approach. The employed metric is sum rate, which is normally a dubious metric for cellular systems, but surprisingly we show that even with this reward function the adaptive strategy also improves fairness. When the channel information is provided by limited feedback, the impact of the induced quantization error is also investigated. It is shown that ICIC with welldesigned feedback strategies still provides significant throughput gain. Index Terms Cellular network, othercell interference, base station coordination, interference cancellation, limited feedback. I.