Weighted Sum MSE Minimization under Per-BS Power Constraint for Network MIMO Systems

• Published in: IEEE communications letters Vol. 16; no. 3; pp. 360 - 363
• Main Authors: PARK, Haewook, PARK, Seok-Hwan, KONG, Han-Bae, LEE, Inkyu
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.03.2012; Institute of Electrical and Electronics Engineers
• Subjects: Applied sciences; Channel estimation; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Information, signal and communications theory; Measurement; MIMO; Minimization; Network MIMO; Optimization; Signal and communications theory; Signal to noise ratio; Signal, noise; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Transceivers; Transmission and modulation (techniques and equipments); weighted sum mean square error (MSE) minimization; Performance evaluation; MIMO system; Estimation error; Parameter estimation; Base station; Feedback regulation; Network MIMO; Iterative method; Algorithm; Mismatching; Optimization; Mean square error; Networked system; Electrical network; Simulation; Channel estimation; Optimal solution; weighted sum mean square error (MSE) minimization; Metric; Gradient method
• ISSN: 1089-7798; 1558-2558
• DOI: 10.1109/LCOMM.2012.010512.112300

We study joint processing (JP) for network MIMO systems where base stations exchange the user's message and channel state information under per-BS power constraint. In this letter, we propose a weighted sum mean square error (WS-MSE) minimization algorithm for the JP systems by considering the channel gain as the weight factor in the MSE metric. To efficiently solve the formulated WS-MSE problem, an alternating optimization method which iteratively finds a local optimal solution is employed in our algorithm. The simulation results confirm that the proposed algorithm provides the sum rate performance close to the near-optimal gradient ascent approach and outperforms conventional schemes. In addition, we also propose a modified WS-MSE design which is robust to channel mismatch caused by channel estimation and feedback errors.