A Novel Fuzzy Inference-Based Technique for Dynamic Link Adaptation in SDR Wideband Waveform

A new dynamic link adaptation technique based on a fuzzy inference system for hybrid multicode code division multiple access/time division multiple access wideband networking waveform of software defined radio is proposed. A constrained optimization problem is formulated under the quality of service, signal-to-noise ratio, and throughput constraints. The optimization problem is solved using the fuzzy inference system by dynamically changing the modulation technique and the number of multicodes assigned to each user. The proposed algorithm provides maximum possible data throughput as required by the user or application by reducing the packet retransmission overhead through the use of optimum waveform parameters decided through the fuzzy inference system. A novel contribution of the proposed algorithm is that it reduces the computational complexity and thus the power consumption by restricting the throughput to the required value even if the channel conditions are fair enough to allow higher throughput. Simulation results are presented to demonstrate the effectiveness of the proposed algorithm in achieving better throughput by efficiently reducing the packet retransmissions overhead.