An intelligent geographic load balance scheme for mobile cellular networks

In this paper, we investigate a novel geographic load balance scheme, which intelligently changes cellular coverage according to the geographic traffic distribution in real time. The performance of the whole cellular network can be improved by contracting the antenna pattern around the source of peak traffic and expanding adjacent cells coverage to fill in the coverage loss. Our previous global optimization work based on scenarios with non-uniformly distributed traffic scenarios has shown the improvement of system capacity of such a dynamical cellular coverage planning scheme exceeds 20%. A cooperative negotiation approach for the real-time control of cellular network coverage is described in this paper. By the use of real time negotiations between base stations and associated antennas, some optimum local coverage agreements can be reached in the context of the whole cellular network.The simulation results using 200 continuous traffic snapshots are presented and followed by some conclusions finally.

[1]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[2]  Ryuji Kohno,et al.  Dynamic cell-size control according to geographical mobile distribution in a DS/CDMA cellular system , 1998, Ninth IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (Cat. No.98TH8361).

[3]  Michael T. Chryssomallis,et al.  Smart antennas , 2000 .

[4]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[5]  Laurie G. Cuthbert,et al.  Cell size and shape adjustment depending on call traffic distribution , 2002, 2002 IEEE Wireless Communications and Networking Conference Record. WCNC 2002 (Cat. No.02TH8609).

[6]  Brahim Chaib-draa,et al.  An overview of distributed artificial intelligence , 1996 .

[7]  Andrew S. Tanenbaum,et al.  Distributed operating systems , 2009, CSUR.

[8]  Krithi Ramamritham,et al.  Distributed Scheduling of Tasks with Deadlines and Resource Requirements , 1989, IEEE Trans. Computers.