Distributed Beamforming Coordination in Multicell MIMO Channels (original) (raw)
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Distributed multicell beamforming with limited intercell coordination
2011
This paper studies distributed optimization schemes for multicell joint beamforming and power allocation in time-division-duplex (TDD) multicell downlink systems where only limited-capacity intercell information exchange is permitted. With an aim to maximize the worst-user signal-to-interference-and-noise ratio (SINR), we devise a hierarchical iterative algorithm to optimize downlink beamforming and intercell power allocation jointly in a distributed manner. The proposed scheme is proved to converge to the global optimum. For fast convergence and to reduce the burden of intercell parameter exchange, we further propose to exploit previous iterations adaptively. Results illustrate that the proposed scheme can achieve near-optimal performance even with a few iterations, hence providing a good tradeoff between performance and backhaul consumption. The performance under quantized parameter exchange is also examined.
Interference Pricing Mechanism for Downlink Multicell Coordinated Beamforming
IEEE Transactions on Communications, 2000
We consider the downlink coordinated beamforming problem in a cellular network in which the base stations (BSs) are equipped with multiple antennas and each user is equipped with a single antenna. The BSs cooperate in sharing their local interference information, and they aim to maximize the sumrate of the users in the network. A decentralized interference pricing beamforming (IPBF) algorithm is proposed to identify the coordinated beamformer, where a BS is penalized according to the interference it creates to its peers. We show that the decentralized pricing mechanism converges to an interference equilibrium, which is a KKT point of the sum-rate maximization problem. The proofs rely on the identification of rank-1 solutions of each BSs' interference-penalized rate maximization problem. Numerical results show that the proposed iterative mechanism reduces significantly the exchanged information with respect to other state-of-the-art beamforming algorithms with very little sum-rate loss. The version of the algorithm that limits the coordination to a cluster of base stations (IPBF-L) is shown to have very small sum-rate loss with respect to the full coordinated algorithm with much less backhaul information exchange.
Partial coordination in clustered base station MIMO transmission
2013
We present partial coordination strategies in a clustered cellular environment, evaluating the achievable rate in the downlink transmission. Block Diagonalization is employed for the coordinated users within the cluster to remove interference, while the interference from non-coordinated users remains. The achievable rate is evaluated resorting to an analytical expression conditioned on the position of the users in the cluster. A partial coordination approach is proposed to reduce the coordination complexity and overhead, where users close to the base station are not coordinated. Two approaches are considered, namely the non-coordinated users can be grouped and assigned separated resources from the coordinated ones, or they can be mixed.
Distributed Beamforming Based on Signal-to Caused-Interference Ratio
2008 IEEE 10th International Symposium on Spread Spectrum Techniques and Applications, 2008
This paper presents a distributed beamforming technique that addresses the effect of inter-cell interference on the downlink of cellular communications systems. The beamforming weights are computed in a distributed manner at each transmit sector antenna array without the need for intersector communication. The beamforming weights are chosen to compromise between maximizing the power to the served user from each sector while minimizing the interference caused to users served in adjacent sectors. The extensions of this method for variable levels of channel state information feedback and multiple receiver antennas are introduced. Beamforming codebooks with power variations across antennas are presented. We show how users can additionally feed back the fraction of interference caused by each interfering sector to incorporate the urgency of interference avoidance into the transmitter optimization.
Min-max fair coordinated beamforming in cellular systems via large systems analysis
2012
This paper considers base station (BS) cooperation in the form of coordinated beamforming, focusing on min-max fairness in the power usage subject to target SINR constraints. We show that the optimal beamforming strategies have an interesting nested zero-forcing structure. In the asymptotic regime where the number of antennas at each BS and the number of users in each cell both grow large with their ratio tending to a finite constant, the dimensionality of the optimization is greatly reduced, and only knowledge of statistics is required to solve it. The optimal solution is characterized in general, and an algorithm is proposed that converges to the optimal transmit parameters, for feasible SINR targets. For the two cell case, a simple single parameter characterization is obtained. These asymptotic results provide insights into the average performance, as well as simple but efficient beamforming strategies for the finite system case. In particular, the optimal beamforming strategy from the large systems analysis only requires the base stations to have local instantaneous channel state information; the remaining parameters of the beamformer can be calculated using channel statistics which can easily be shared amongst the base stations.
Joint beamforming design and base-station assignment in a coordinated multicell system
IET Communications, 2013
This study is concerned with the downlink beamforming designs in a coordinated multicell system with dynamic basestation (BS) assignment. At each cell, a multiple-antenna BS employs linear beamforming to send multiple data streams to its assigned mobile-stations (MSs). Exploiting multicell coordination, the multiple BSs jointly optimise the beamformers and the BS-MS assignments to enhance the overall system performance. With per-BS power constraints, considered are the coordinated beamforming problems under the following two design criteria: (i) minimising the transmit power margin at the BS with a set of target signal-to-interference-plus-noise ratios (SINR) at the MSs and (ii) jointly maximising the minimum SINR margin at the MSs. As the original problem formulations are shown to be non-convex integer programs, which are combinatorially hard, the authors propose an efficient convex relaxation approach to solve the problems with low complexity. Simulations show that the convex relaxation-based assignment schemes significantly outperform heuristic fixed assignment schemes.
2016
We consider the coordinated downlink beamforming problem in a cellular network with the base stations (BSs) equipped with multiple antennas, and with each user equipped with a single antenna. The BSs cooperate in sharing their local interference information, and they aim at maximizing the sum rate of the users in the network. A set of new lower bounds (one bound for each BS) of the non-convex sum rate is identified. These bounds facilitate the development of a set of algorithms that allow the BSs to update their beams by optimizing their respective lower bounds. We show that when there is a single user per-BS, the lower bound maximization problem can be solved exactly with rank-1 solutions. In this case, the overall sum rate maximization problem can be solved to a KKT point. Numerical results show that the proposed algorithms achieve high system throughput with reduced backhaul information exchange among the BSs.
Competitive Downlink Beamforming Design in Multiuser Multicell Wireless Systems
2010 IEEE Global Telecommunications Conference GLOBECOM 2010, 2010
This paper is concerned with the game-theory approach in designing the multiuser downlink beamformers in multicell systems. Sharing the same physical resource, the base station of each cell wishes to minimize its transmit power subject to a set of target signal-to-interference-plus-noise ratios (SINRs) at the multiple users in the cell. In that process, each base station determines its optimal downlink beamformer strategy in a distributed manner, without any coordination between the cells. Via the game-theory framework, we examine the conditions guaranteeing the existence and uniqueness of the Nash Equilibrium (NE). We establish the best response strategy of a cell, given the beamforming strategies from other cells. Such best response strategy is shown to be a standard function, which then guarantees the uniqueness of the NE and the convergence of the distributed algorithm. A sufficient condition for the existence of the NE is also presented.
Sum-Rate Maximization in the Multicell MIMO Broadcast Channel With Interference Coordination
IEEE Transactions on Signal Processing, 2014
This paper studies the precoding designs to maximize the weighted sum-rate (WSR) in a multicell multiple-input multiple-output (MIMO) broadcast channel (BC). We consider a multicell network under universal frequency reuse with multiple mobile stations (MS) per cell. With interference coordination (IC) between the multiple cells, the base-station (BS) at each cell only transmits information signals to the MSs within its cell using the dirty paper coding (DPC) technique, while coordinating the intercell interference (ICI) induced to other cells. The main focus of this work is to jointly optimize the encoding covariance matrices across the BSs in order to maximize the network-wide WSR. Since this optimization problem is shown to be nonconvex, obtaining its globally optimal solution is highly complicated. To address this problem, we consider two low-complexity solution approaches with distributed implementation to obtain at least locally optimal solutions. In the first approach, by applying a successive convex approximation technique, the original nonconvex problem is decomposed into a sequence of simpler problems, which can be solved optimally and separately at each BS. In the second approach, the WSR problem is solved via an equivalent problem of weighted sum mean squared error minimization. Both solution approaches will unfold the control signaling among the coordinated BSs to allow their distributed implementation. Simulation results confirm the convergence of the proposed algorithms, as well as their superior performances over schemes with linear precoding or no interference coordination among the BSs.