DocumentCode :
1442085
Title :
Searching for optimal frame patterns in an integrated TDMA communication system using mean field annealing
Author :
Wang, Gangsheng ; Ansari, Nirwan
Author_Institution :
Multimedia Commun. Dept., Sharp Lab. of America Inc., Camas, WA, USA
Volume :
9
Issue :
6
fYear :
1998
fDate :
11/1/1998 12:00:00 AM
Firstpage :
1292
Lastpage :
1300
Abstract :
In an integrated time-division multiple access (TDMA) communication system, voice and data are multiplexed in time to share a common transmission link in a frame format in which time is divided into slots. A certain number of time slots in a frame are allocated to voice and the rest are used to transmit data. Maximum data throughput can be achieved by searching for the optimal configuration(s) of relative positions of voice and data transmissions in a frame (frame pattern). When the problem size becomes large, the computational complexity in searching for the optimal patterns becomes intractable. In the paper, mean field annealing (MFA), which provides near-optimal solutions with reasonable complexity, is proposed to solve this problem. The determination of the related parameters are addressed. Comparison with the random search and simulated annealing algorithm is made in terms of solution optimality and computational complexity. Simulation results show that the MFA approach exhibits a good tradeoff between performance and computational complexity
Keywords :
ISDN; combinatorial mathematics; computational complexity; neural nets; optimisation; search problems; time division multiple access; computational complexity; data transmissions; integrated TDMA communication system; integrated time-division multiple access communication system; maximum data throughput; mean field annealing; near-optimal solutions; optimal configuration; optimal frame patterns; time slots; voice transmission; Computational complexity; Computational modeling; Data communication; Delay; Optimization methods; Simulated annealing; Stochastic processes; Throughput; Time division multiple access; Traffic control;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.728379
Filename :
728379
Link To Document :
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