Cooperative Multi-Cell Block Diagonalization with Per-Base-Station Power Constraints

Block diagonalization (BD) is a practical linear precoding technique that eliminates the inter-user interference in downlink multiuser multiple-input multiple-output (MIMO) systems. In this paper, we apply BD to the downlink transmission in a cooperative multi-cell MIMO system, where the signals from different base stations (BSs) to all the mobile stations (MSs) are jointly designed with the perfect knowledge of the downlink channels and transmit messages. Specifically, we study the optimal BD precoder design to maximize the weighted sum-rate of all the MSs subject to a set of per-BS power constraints. This design problem is formulated in an auxiliary MIMO broadcast channel (BC) with a set of transmit power constraints corresponding to those for individual BSs in the multi-cell system. By applying convex optimization techniques, this paper develops an efficient algorithm to solve this problem, and derives the closed-form expression for the optimal BD precoding matrix. It is revealed that the optimal BD precoding vectors for each MS in the per-BS power constraint case are in general non-orthogonal, which differs from the conventional orthogonal BD precoder design for the MIMO-BC under one single sum-power constraint. Moreover, for the special case of single-antenna BSs and MSs, the proposed solution reduces to the optimal zero-forcing beamforming (ZF-BF) precoder design for the weighted sum-rate maximization in the multiple-input single-output (MISO) BC with per-antenna power constraints. Suboptimal and low-complexity BD/ZF-BF precoding schemes are also presented, and their achievable rates are compared against those with the optimal schemes.Comment: accepted in JSAC, special issue on cooperative communications on cellular networks, June 201

SWIPT techniques for multiuser MIMO broadcast systems

In this paper, we present an approach to solve the nonconvex optimization problem that arises when designing the transmit covariance matrices in multiuser multiple-input multiple-output (MIMO) broadcast networks implementing simultaneous wireless information and power transfer (SWIPT). The MIMO SWIPT design is formulated as a nonconvex optimization problem in which system sum rate is optimized considering per-user harvesting constraints. Two different approaches are proposed. The first approach is based on a classical gradient-based method for constrained optimization. The second approach is based on difference of convex (DC) programming. The idea behind this approach is to obtain a convex function that approximates the nonconvex objective and, then, solve a series of convex subproblems that, eventually, will provide a (locally) optimum solution of the general nonconvex problem. The solution obtained from the proposed approach is compared to the classical block-diagonalization (BD) strategy, typically used to solve the nonconvex multiuser MIMO network by forcing no inter-user interference. Simulation results show that the proposed approach improves both the system sum rate and the power harvested by users simultaneously. In terms of computational time, the proposed DC programming outperforms the classical gradient methods.Peer ReviewedPostprint (author's final draft

Indoor Massive MIMO Deployments for Uniformly High Wireless Capacity

Providing consistently high wireless capacity is becoming increasingly important to support the applications required by future digital enterprises. In this paper, we propose Eigen-direction-aware ZF (EDA-ZF) with partial coordination among base stations (BSs) and distributed interference suppression as a practical approach to achieve this objective. We compare our solution with Zero Forcing (ZF), entailing neither BS coordination or inter-cell interference mitigation, and Network MIMO (NeMIMO), where full BS coordination enables centralized inter-cell interference management. We also evaluate the performance of said schemes for three sub-6 GHz deployments with varying BS densities -- sparse, intermediate, and dense -- all with fixed total number of antennas and radiated power. Extensive simulations show that: (i) indoor massive MIMO implementing the proposed EDA-ZF provides uniformly good rates for all users; (ii) indoor network densification is detrimental unless full coordination is implemented; (iii) deploying NeMIMO pays off under strong outdoor interference, especially for cell-edge users

Achievable rate and fairness in coordinated base station transmission

This work focuses on the fairness in the distribution of the achievable rate per user in a cellular environment where clusters of base stations coordinate their transmissions in the downlink. Block Diagonalization is employed within the cluster to remove interference among users while the interference coming from other clusters remains. The probability distribution of the achievable rate per user shows a perfect match with a Gamma distribution so that a characterization in terms of mean and variance can provide a useful tool for the design of the clusters and the implementation of fairness strategies in a coordinated base station network with Block Diagonalization.This work is partly funded by the projects “GRE3N”: TEC2011-29006- C03-03, and “COMONSENS”: CSD2008-00010.Publicad

Performance evaluation of multicell coordinated beamforming approaches for OFDM systems

In this paper we propose and evaluate multicell coordinated beamforming schemes for the downlink of MISO-OFDM systems. The precoders are designed in two phases: first the precoder vectors are computed in a distributed manner at each BS considering two criteria, namely distributed zero-forcing and virtual signal-to-interference noise ratio. Then the system is optimized through distributed power allocation under per-BS power constraint. The proposed power allocation scheme is designed based on minimization of the average bit error rate over all the available subcarriers. Both the precoder vectors and the power allocation are computed by assuming that the BSs have only knowledge of local channel state information and do not share the data symbols. The performance of the proposed schemes are evaluated, considering typical pedestrian scenarios based on LTE specifications. The results have shown that the proposed distributed power allocation scheme outperform the equal power allocation approach

Power allocation for coordinated multi-cell systems with imperfect channel and battery-capacity-limited receivers

This letter studies the transmit power allocation in downlink coordinated multi-cell systems with the batterycapacity-limited receivers, where the battery level of receivers is considered. The power allocation is formulated as an optimization problem to maximize the minimum signal-to-interference noise ratio of users under the per-base station power constraints and the feasible maximum received data rate constraints determined by the receiver battery level. The optimal solutions are derived by the proposed monotonic optimization technique based algorithm. The proposed algorithm can extend the battery lifetime of the receivers with lower battery level. Simulation results illustrate the performance of the proposed algorithm

Group Sparse Precoding for Cloud-RAN with Multiple User Antennas

Cloud radio access network (C-RAN) has become a promising network architecture to support the massive data traffic in the next generation cellular networks. In a C-RAN, a massive number of low-cost remote antenna ports (RAPs) are connected to a single baseband unit (BBU) pool via high-speed low-latency fronthaul links, which enables efficient resource allocation and interference management. As the RAPs are geographically distributed, the group sparse beamforming schemes attracts extensive studies, where a subset of RAPs is assigned to be active and a high spectral efficiency can be achieved. However, most studies assumes that each user is equipped with a single antenna. How to design the group sparse precoder for the multiple antenna users remains little understood, as it requires the joint optimization of the mutual coupling transmit and receive beamformers. This paper formulates an optimal joint RAP selection and precoding design problem in a C-RAN with multiple antennas at each user. Specifically, we assume a fixed transmit power constraint for each RAP, and investigate the optimal tradeoff between the sum rate and the number of active RAPs. Motivated by the compressive sensing theory, this paper formulates the group sparse precoding problem by inducing the $\ell_0$-norm as a penalty and then uses the reweighted $\ell_1$ heuristic to find a solution. By adopting the idea of block diagonalization precoding, the problem can be formulated as a convex optimization, and an efficient algorithm is proposed based on its Lagrangian dual. Simulation results verify that our proposed algorithm can achieve almost the same sum rate as that obtained from exhaustive search

Improved Linear Precoding over Block Diagonalization in Multi-cell Cooperative Networks

In downlink multiuser multiple-input multiple-output (MIMO) systems, block diagonalization (BD) is a practical linear precoding scheme which achieves the same degrees of freedom (DoF) as the optimal linear/nonlinear precoding schemes. However, its sum-rate performance is rather poor in the practical SNR regime due to the transmit power boost problem. In this paper, we propose an improved linear precoding scheme over BD with a so-called "effective-SNR-enhancement" technique. The transmit covariance matrices are obtained by firstly solving a power minimization problem subject to the minimum rate constraint achieved by BD, and then properly scaling the solution to satisfy the power constraints. It is proved that such approach equivalently enhances the system SNR, and hence compensates the transmit power boost problem associated with BD. The power minimization problem is in general non-convex. We therefore propose an efficient algorithm that solves the problem heuristically. Simulation results show significant sum rate gains over the optimal BD and the existing minimum mean square error (MMSE) based precoding schemes.Comment: 21 pages, 4 figure

Power allocation for coordinated multi-cell systems with imperfect channel and battery-capacity-limited receivers

This letter studies the transmit power allocation in downlink coordinated multi-cell systems with the batterycapacity-limited receivers, where the battery level of receivers is considered. The power allocation is formulated as an optimization problem to maximize the minimum signal-to-interference noise ratio of users under the per-base station power constraints and the feasible maximum received data rate constraints determined by the receiver battery level. The optimal solutions are derived by the proposed monotonic optimization technique based algorithm. The proposed algorithm can extend the battery lifetime of the receivers with lower battery level. Simulation results illustrate the performance of the proposed algorithm