4.7 Article

Joint Beamforming and Power Splitting for MISO Interference Channel With SWIPT: An SOCP Relaxation and Decentralized Algorithm

Journal

IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume 62, Issue 23, Pages 6194-6208

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2014.2362092

Keywords

Beamforming; distributed algorithm; dynamic power splitting; MISO interference channel; simultaneous wireless information and power transfer; SOCP

Funding

  1. National Nature Science Foundation of China [61302076, 61374020, 61372135, 61473197]
  2. Key Project of Chinese Ministry of Education [212066]
  3. Zhejiang Provincial Natural Science Foundation of China [LY12F02042, LQ12F01009, LQ13F010008]
  4. Science Foundation of Zhejiang Sci-Tech University (ZSTU) [1203805Y]
  5. State Key Laboratory of Integrated Services Networks, Xidian University [ISN14-08]
  6. Ministry of Science and Technology, Taiwan [NSC 102-2221-E-011-005-MY3]

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This paper considers a power splitting-based MISO interference channel for simultaneous wireless information and power transfer (SWIPT), where each single antenna receiver splits the received signal into two streams of different power for decoding information and harvesting energy separately. We aim to minimize the total transmission power by joint beamforming and power splitting (JBPS) under both the signal-to-interference-plus-noise ratio (SINR) constraints and energy harvesting (EH) constraints. The JBPS problem is nonconvex and has not yet been well addressed in the literature. Moreover, decentralized algorithm design for JBPS based on local channel state information (CSI) and limited information exchange remains open. In this paper, we first propose a novel relaxation method named second-order cone programming (SOCP) relaxation to address the JBPS problem. We formulate the relaxed problem as an SOCP and present two sufficient conditions under which the SOCP relaxation is tight. For the case when the SOCP solution is not necessarily optimal to the JBPS problem, a closed-form feasible-solution-recovery method is provided. Then, we develop a distributed algorithm for the JBPS problem based on primal-decomposition (PD) method. The PD-based distributed algorithm consists of a master problem and a set of subproblems. The former is solved by using subgradient method while the latter are solved using coordinate descent method. Finally, numerical results validates the efficiency of the proposed algorithms.

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