Robust Distributed Beamforming With Interference Coordination in Downlink Cellular Networks

• Published in: IEEE transactions on communications Vol. 62; no. 7; pp. 2411 - 2421
• Main Authors: Shaverdian, Ararat, Nakhai, Mohammad Reza
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.07.2014; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Array signal processing; Beamforming; Detection, estimation, filtering, equalization, prediction; Downlink; Equipments and installations; Errors; Exact sciences and technology; Information, signal and communications theory; Interference; Joining; Mathematical models; Mobile radiocommunication systems; Optimization; Radiocommunication specific techniques; Radiocommunications; Robustness; Signal and communications theory; Signal to noise ratio; Signal, noise; Stations; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Transmission and modulation (techniques and equipments); Vectors; coordinated multipoint communications; Convex optimization; distributed robust beamforming; Performance evaluation; Parameter estimation; Base station; Wireless telecommunication; Downlink; Iterative method; Cell network; Convex programming; Data broadcast; Beam forming; Optimization; Relaxation; Channel estimation; Intercell interference; Gradient method; Information exchange; Mobile radiocommunication; Intercarrier interference; Algorithm; Simulation; Telecommunication network; Signal to interference plus noise ratio; Software radio
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2014.2326875

This paper focuses on multicell coordinated beamforming in the presence of channel state information (CSI) errors, where base stations (BSs) collaboratively mitigate their intercell interference (ICI). Assuming that the CSI errors are hyper-spherically bounded, we consider an optimization problem that minimizes the overall transmission power of BSs subject to signal-to-interference-plus-noise-ratio (SINR) constraints at each mobile station (MS). We solve this problem in a distributed manner with a limited information exchange among BSs. Using semidefinite relaxation (SDR) and the S-Lemma, we first reformulate our optimization problem into a numerically tractable one. Since the SINR constraints are coupled, we introduce an algorithm by which each BS can obtain a local version of its coupling variables via a small data exchange with other BSs. Then, we propose an iterative algorithm that employs the projected gradient method to coordinate ICI across multiple BSs. Finally, we extend the application of the proposed algorithm to solve the problem of robust and distributed per-user SINR maximization under per-BS power constraints. Simulation results confirm the effectiveness of the proposed algorithm in terms of power efficiency and convergence in the presence of CSI uncertainties.