Energy-efficient distributed multicast beamforming using iterative second-order cone programming
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چکیده
In multi-user (MU) downlink beamforming, a high spectral efficiency along with a low transmit power is achieved by separating multiple users in space rather than in time or frequency using spatially selective transmit beams. For streaming media applications, multi-group multicast (MGM) downlink beamforming is a promising approach to exploit the broadcasting property of the wireless medium to transmit the same information to a group of users. To limit inter-group interference, the individual streams intended for different multicast groups are spatially separated using MGM downlink beamforming. Spatially selective downlink beamforming requires the employment of an array of multiple antennas at the base station (BS). The hardware costs associated with the use of multiple antennas may be prohibitive in practice. A way to avoid the expensive employment of multiple antennas at the BS is to exploit user cooperation in wireless networks where multiple single-antenna users act as relays and take over the role of antenna elements in a virtual distributed antenna array. In both downlink beamforming and distributed relay beamforming, several approaches to design the transmit beams exist. In many scenarios, minimizing the transmit power has a higher priority than maximizing throughput. This is the case, e.g., in downlink beamforming, when operators aim at reducing their operational expenditures and their carbon footprint, or in distributed beamforming when users are only willing to cooperate when the battery consumption of their devices is kept at a minimum level. Then, the transmit beams are designed as the solution of a quality-of-service-constrained (QoSconstrained) power minimization problem. The goal of this optimization approach is to minimize the total transmitted power (at the BS or at the relays) while guaranteeing a predefined QoS at the destination users. In many scenarios with a high relevance in practice such as MGM downlink beamforming and MU peer-to-peer (MUP2P) relay beamforming, the QoS-constrained power minimization problem is a nonconvex optimization problem which cannot be solved optimally in polynomial time. In stateof-the-art methods, the nonconvex problem is therefore approximated by a convex one which is easier to solve. As the number of users increases, however, these approximations become more and more inaccurate leading to severe performance degradation and problem infeasibility. In this dissertation, we therefore propose a novel framework of iterative optimization schemes where a convex approximation of the original problem is successively improved. In each iteration of the proposed schemes, a convex approximation of the original problem is solved and then adapted to the solution obtained in this iteration. We prove that by this means, the approximate solution is improved from iteration to
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تاریخ انتشار 2015