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 this 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.
Original language | English (US) |
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Pages (from-to) | 1292-1300 |
Number of pages | 9 |
Journal | IEEE Transactions on Neural Networks |
Volume | 9 |
Issue number | 6 |
DOIs | |
State | Published - 1998 |
All Science Journal Classification (ASJC) codes
- Software
- Computer Science Applications
- Computer Networks and Communications
- Artificial Intelligence
Keywords
- Combinatorial optimization
- Energy function
- Frame pattern
- Mean field annealing
- Neural networks
- Simulated annealing
- Time division multiple access