Optimization for beamforming problems in wireless networks

Beamforming in wireless communications have gathered great interests in recent years due to its ability to enhanced the performance of networks significantly by exploiting intensively the spatial diversity. In this work, the objectives of beamforming design consist of several optimization targets ranging from minimizing the beamforming power subject to quality-of-service (QoS) constraints to maximizing the minimum QoS regarding fixed budgets of transmitting power. The design problems of beamforming are intrinsically challenging because their natural formulations are nonconvex optimization problems. Moreover several problems are proved to be non-deterministic polynomial-time hard (NP-hard) such as beamforming in multicast transmission. These problems are very difficult to solve at optimality in practical sense. Therefore, there is a strong motivation to convert the original design problems into a series of convex problems with desirable computational complexity by applying efficient optimization techniques. This dissertation contributes mainly in exploiting the convex optimization algorithms to solve nonconvex beamforming problems in several network settings. First, the transmit beamforming for downlink communication of multicast transmission with spectrum sharing is investigated. Secondly, the beamforming design is applied on amplify-forward (AF) wireless relaying systems using single-antenna relays. The key contribution is to derive the beamforming schemes applied on transmit antennas so that the beamforming power is minimized while all users' signal-to-interference-and-noise ratios (SINRs) are guaranteed. The formulation results in nonconvex optimization problems due to SINR constraints hence require to be converted into semidefinite programming (SDP) forms. The SDP problems are again nonconvex regarding the rank-one constraints on semidefinite variables. Conventionally, the rank-one constraints are relaxed hence the problems cannot be solved thoroughly. In this work, nonsmooth optimization techniques are employed to tackle with the nonconvex rank-one constraints and are successfully to deliver efficient solutions that can outperform the conventional methods. Finally the precoding design problems in mutiple-input multiple-output (MIMO) relaying scenarios are considered. The difference-of-two-convex-function (D.C.) programming technique is employed to solve the problems at optimality with significantly lower complexity compared with conventional method

Space-time beamforming for multiuser wireless relay networks

The paper is concerned with a multiuser communication network, which is assisted by multiple relays. It has been observed through our previous related works that the conventional simultaneous beamforming at parallel amply-and-forward (AF) relays is not quite effective and often infeasible to target practically desirable signal-to-interference-and-noise ratio (SINR) at the destinations. To overcome this shortage, we propose the time-division for multiple-user transmission to the relays so the later can perform beamforming on signals received from the individuals and then parallelly forward its combinations at once to the destinations. The optimal beamforming problem is a nonconvex quadratically constrained optimization, which is globally solved by our tailored algorithm of nonsmooth optimization. Its found global optimal solutions are shown very effective and over-perform other possible multi-user relay beamformings. © 2011 IEEE