Now showing 1 - 5 of 5
- PublicationMulti-group multicast beamformer design for MIMO-OFDM transmissionWe study the problem of designing multicast precoders for multiple groups with the objective of minimizing total transmit power under certain guaranteed quality-of-service (QoS) requirements. To avail both spatial and frequency diversity, we consider a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. The problem of interest is in fact a nonconvex quadratically constrained quadratic program (QCQP) for which the prevailing semidefinite relaxation (SDR) technique is inefficient for at least two reasons. At first, the relaxed problem cannot be equivalently reformulated as a semidefinite programming (SDP). Secondly, even if the relaxed problem is solved, the so-called randomization procedure should be used to generate a high quality feasible solution to the original QCQP. However, such a randomization procedure is difficult in the considered system model. To overcome these shortcomings, we adopt successive convex approximation (SCA) framework in this paper to find beamformers directly. The proposed method not only avoids the randomization procedure mentioned above but also requires lower computational complexity compared to the SDR approach. Numerical experiments are carried out to demonstrate the effectiveness of the proposed algorithm.
- PublicationMultigroup Multicast Beamformer Design for MISO-OFDM With Antenna SelectionWe study the problem of designing transmit beamformers for a multigroup multicasting by considering a multiple-input single-output orthogonal frequency-division multiplexing framework. The design objective involves either minimizing the total transmit power for certain guaranteed quality of service or maximizing the minimum achievable rate among the users for a given transmit power budget. The problem of interest can be formulated as a nonconvex quadratically constrained quadratic programming (QCQP) for which the prevailing semidefinite relaxation (SDR) technique is inefficient for at least two reasons. At first, the relaxed problem cannot be reformulated as a semidefinite programming. Second, even if the relaxed problem is solved, the so-called randomization procedure should be used to generate a feasible solution to the original QCQP, which is difficult to derive for the considered problem. To overcome these shortcomings, we adopt successive convex approximation framework to find multicast beamformers directly. The proposed method not only avoids the need of randomization search, but also incurs less computational complexity compared to an SDR approach. In addition, we also extend multicasting beamformer design problem with an additional constraint on the number of active elements, which is particularly relevant when the number of antennas is larger than that of radio frequency chains. Numerical results are used to demonstrate the superior performance of our proposed methods over the existing solutions.
Scopus© Citations 23 388
- PublicationEnergy-Efficient Beam Coordination Strategies With Rate-Dependent Processing PowerThis paper proposes energy-efficient coordinated beamforming strategies for multicell multiuser multiple-input single-output system. We consider a practical power consumption model, where part of the consumed power depends on the base station or user specific data rates due to coding, decoding, and backhaul. This is different from the existing approaches where the base station power consumption has been assumed to be a convex or linear function of the transmit powers. Two optimization criteria are considered, namely network energy efficiency maximization and weighted sum energy efficiency maximization. We develop successive convex approximation-based algorithms to tackle these difficult nonconvex problems. We further propose decentralized implementations for the considered problems, in which base stations perform parallel and distributed computation based on local channel state information and limited backhaul information exchange. The decentralized approaches admit closed-form solutions and can be implemented without invoking a generic external convex solver. We also show an example of the pilot contamination effect on the energy efficiency using a heuristic pilot allocation strategy. The numerical results are provided to demonstrate that the rate dependent power consumption has a large impact on the system energy efficiency, and, thus, has to be taken into account when devising energy-efficient transmission strategies. The significant gains of the proposed algorithms over the conventional low-complexity beamforming algorithms are also illustrated.
387Scopus© Citations 28
- PublicationTraffic Aware Resource Allocation Schemes for Multi-Cell MIMO-OFDM SystemsWe consider a downlink multi-cell multiple-input multiple-output (MIMO) interference broadcast channel (IBC) using orthogonal frequency division multiplexing (OFDM) with multiple users contending for space-frequency resources in a given scheduling instant. The problem is to design precoders efficiently to minimize the number of backlogged packets queuing in the coordinating base stations (BSs). Conventionally, the queue weighted sum rate maximization (Q-WSRM) formulation with the number of backlogged packets as the corresponding weights is used to design the precoders. In contrast, we propose joint space-frequency resource allocation (JSFRA) formulation, in which the precoders are designed jointly across the space-frequency resources for all users by minimizing the total number of backlogged packets in each transmission instant, thereby performing user scheduling implicitly. Since the problem is nonconvex, we use the combination of successive convex approximation (SCA) and alternating optimization (AO) to handle nonconvex constraints in the JSFRA formulation. In the first method, we approximate the signal-to-interference-plus-noise ratio (SINR) by convex relaxations, while in the second approach, the equivalence between the SINR and the mean squared error (MSE) is exploited. We then discuss the distributed approaches for the centralized algorithms using primal decomposition and alternating directions method of multipliers. Finally, we propose a more practical iterative precoder design by solving the Karush-Kuhn-Tucker expressions for the MSE reformulation that requires minimal information exchange for each update. Numerical results are used to compare the proposed algorithms to the existing solutions.
Scopus© Citations 41 237
- PublicationEnergy-efficient coordinated beamforming with rate dependent processing powerThis paper studies energy-efficient coordinated beamforming in multi-cell multi-user multiple-input single-output (MISO) system. On contrary to the existing approaches where the power consumption of a base station is modeled as a convex or linear function, we consider a more practical model where part of the processing power depends on the rate provided by the base stations. Two optimization criteria are considered, namely network energy efficiency maximization and weighted sum energy efficiency maximization. We develop successive convex approximation based algorithms to tackle these difficult nonconvex problems. The numerical results illustrate that the rate dependent power consumption has a large impact on the energy efficiency, and, thus, has to be taken into account when devising energy-efficient transmission strategies.
145Scopus© Citations 8