An Efficient Precoder Design for Multiuser MIMO Cognitive Radio Networks With Interference Constraints
- Authors
- Van-Dinh Nguyen; Le-Nam Tran; Duong, Trung Q.; Shin, Oh-Soon; Farrell, Ronan
- Issue Date
- May-2017
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Beamforming; broadcast channel (BC); cognitive radio (CR); multiple-input multiple-output (MIMO); sumrate (SR) maximization; zero-forcing (ZF)
- Citation
- IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v.66, no.5, pp.3991 - 4004
- Journal Title
- IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- Volume
- 66
- Number
- 5
- Start Page
- 3991
- End Page
- 4004
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/6388
- DOI
- 10.1109/TVT.2016.2602844
- ISSN
- 0018-9545
- Abstract
- We consider a linear precoder design for an underlay cognitive radio multiple-input multiple-output (MIMO) broadcast channel, where the secondary system consisting of a secondary base station (BS) and a group of secondary users is allowed to share the same spectrum with the primary system. All the transceivers are equipped with multiple antennas, each of which has its own maximum power constraint. Assuming zero-forcing (ZF) method to eliminate the multiuser interference, we study the sum rate maximization problem for the secondary system subject to both per-antenna power constraints at the secondary BS and the interference power constraints at the primary users. The problem of interest differs from the ones studied previously that often assumed a sum power constraint and/or single antenna employed at either both the primary and secondary receivers or the primary receivers. To develop an efficient numerical algorithm, we first invoke the rank relaxation method to transform the considered problem into a convex-concave problem based on a downlink-uplink result. We then propose a barrier interior-point method to solve the resulting saddle point problem. In particular, in each iteration of the proposed method we find the Newton step by solving a system of discrete-time Sylvester equations, which help reduce the complexity significantly, compared to the conventional method. Simulation results are provided to demonstrate fast convergence and effectiveness of the proposed algorithm.
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