Self-optimized MIMO-OFDMA: A Nash-Stackelberg game-theoretic approach

This paper studies self-optimization of resource allocation for multipoint-to-multipoint orthogonal frequency-division multiple-access (OFDMA) interference channels with multiple-input multiple-output (MIMO) user terminals. Each user intends to maximize its achievable rate based on its local observation on the channels and its prediction on how other users would respond. We achieve this by constructing a Nash-Stackelberg (N-S) game in which the Nash part deals with the competition over spatial subchannels of MIMO whereas the Stacklelberg part manages the competition over frequency subcarriers among users. Simulation results demonstrate that an all-Nash game fails to reconcile users´ competition and has flat user rates as a function of signal-to-noise ratio (SNR) but the proposed N-S game can achieve an order of magnitude gain in user rates which also grow with the SNR.