Linear Precoding Bounds for Wyner-Type Cellular Networks With Limited Base-Station Cooperation and Dynamic Clustering

• Published in: IEEE transactions on signal processing Vol. 60; no. 7; pp. 3714 - 3725
• Main Authors: Bergel, I., Yellin, D., Shamai, S.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.07.2012; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Base stations; Cellular; Cellular communication; Cellular networks; Channel models; Coding, codes; Cooperation; cooperative systems; Detection, estimation, filtering, equalization, prediction; Downlink; Exact sciences and technology; Information, signal and communications theory; Interference; Land mobile radio cellular systems; Limiting; Lower bounds; Optimization; Signal and communications theory; Signal representation. Spectral analysis; Signal to noise ratio; Signal, noise; Stations; Telecommunications and information theory; Transaction processing; Work study; Performance evaluation; Automatic classification; Parameter estimation; Base station; Wireless telecommunication; Information rate; Equity; Downlink; Cell network; channel models; Coding; Channel estimation; Pretreatment; Mobile radiocommunication; Lower bound; Coding circuit; Cooperative systems; Signal classification; Information transmission; Cellular networks; Upper bound; Telecommunication network; Signal processing; Numerical simulation; Signal to noise ratio
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2012.2194287

This work studies the achievable average data rate in the downlink of a Wyner-type linear cellular network with limited cooperation and linear precoders. We derive upper and lower bounds on the achievable average data rate subject to an average power constraint. The bounds show that even a small number of cooperating base stations applying suboptimal (linear) precoding can approach optimal performance, and significantly increase the average user data rates as compared to those achievable with noncooperating cellular systems. We highlight the importance of dynamic clustering and of base station (BS) silencing. Dynamic clustering allows the system to build clusters that benefit some users at the expense of others, and then shifts the priority between the users. Such a scheme results in higher average rates for all users, while meeting some level of fairness. BS silencing is shown to be important for limited cooperation networks in the high SNR regime. Silencing is a simple and efficient way to reduce the interference (and hence increase the user rates) without increasing the number of cooperating BSs. The theoretical analysis is accompanied by several numerical examples in selected scenarios.