Capacity Region of MISO Broadcast Channel for Simultaneous Wireless Information and Power Transfer

被引:29
作者
Luo, Shixin [1 ]
Xu, Jie [1 ]
Lim, Teng Joon [1 ]
Zhang, Rui [1 ,2 ]
机构
[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 119077, Singapore
[2] ASTAR, Inst Infocomm Res, Singapore 138632, Singapore
关键词
Multiple input multiple output (MIMO); broadcast channel (BC); dirty paper coding (DPC); capacity region; simultaneous wireless information and power transfer (SWIPT); energy harvesting; uplink-downlink duality; COMMUNICATION; DUALITY; SWIPT;
D O I
10.1109/TCOMM.2015.2461220
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper studies a multiple-input-single-output (MISO) broadcast channel (BC) featuring simultaneous wireless information and power transfer, where a multiantenna access point (AP) delivers both information and energy via radio signals to multiple single-antenna receivers simultaneously, and each receiver implements either information decoding (ID) or energy harvesting (EH). In particular, pseudorandom sequences that are a priori known and therefore can be cancelled at each ID receiver are used as the energy signals, and the information-theoretically optimal dirty paper coding is employed for the information transmission. We characterize the capacity region for ID receivers by solving a sequence of weighted sum-rate (WSR) maximization (WSRMax) problems subject to a maximum sum-power constraint for the AP, and a set of minimum harvested power constraints for individual EH receivers. The problem corresponds to a new form of WSRMax problem in MISO-BC with combined maximum and minimum linear transmit covariance constraints (MaxLTCCs and MinLTCCs), which differs from the celebrated capacity region characterization problem for MISO-BC under a set of MaxLTCCs only and is challenging to solve. By extending the general BC-multiple-access-channel duality, which is only applicable to WSRMax problems with MaxLTCCs, and applying the ellipsoid method, we propose an efficient iterative algorithm to solve this problem globally optimally. Furthermore, we also propose two suboptimal algorithms with lower complexity by assuming that the information and energy signals are designed separately. Finally, numerical results are provided to validate our proposed algorithms.
引用
收藏
页码:3856 / 3868
页数:13
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