Adaptive modulation for MU-MIMO-OFDM systems in Underlay Cognitive Radio Networks

In this paper, a modified rate quantization algorithm for multi-user multiple-input-multiple-output-orthogonal frequency division multiplexing (MU-MIMO-OFDM) cognitive architectures is proposed. Targeting to fulfill the requirements of 5G communications systems and beyond, while keeping a low complexity degree, we first adapt the sub-channel transmit power and spectral efficiency in the spatial and temporal domains under transmit power and instantaneous bit error rate (BER) constraints. We then use a stochastic algorithm to maximize the rate and transmit power of each secondary user (SU) over the spatial eigen-channels of the corresponding subcarrier MIMO channel, under the constraints of average power budget and probability of interference. It is shown that the proposed scheme outperforms the extended rounding-off (SR) alternative, for the entire SNR range.