Cross-Layer Design of Optimal Adaptation Technique over Selection-Combining Diversity Nakagami-m Fading Channels

Adaptive modulation and antenna diversity are two important enabling techniques for future wireless network to meet demand for high data rate transmission. We study a Markov decision process based cross-layer design of optimal adaptation policy over selection-combining Nakagami-m fading channel for Markov modulated Poisson process (MMPP) traffic. Unlike most of the channel-dependent adaptation policy in the literature, proposed policy chooses modulation constellation dynamically depending on the traffic and buffer states in addition to channel state. Proposed cross-layer dynamic adaptation policy minimizes transmission power, maximizes throughput, and also guarantees target bit error rate, delay and packet overflow rate requirements for the application being considered.