Performance of Novel Adaptive Schemes for Cognitive Full-Duplex Relaying-Based Downlink Cooperative NOMA

In this paper, we demonstrate that due to large variations in link signal-to-noise-ratios, the key to good performance in underlay cooperative non-orthogonal multiple access (CNOMA) is intelligent adaptation. First adaptation involves switching between the cooperative mode (CM) and the non-cooperative mode (NCM). While a full-duplex near user (NU) assists the multiple-antenna base-station in communication to a far user (FU) in CM, allowing the NU to switch to NCM ensures that its performance is same as in a network without the FU. The second adaptation relates to transmit antenna selection. In the first scheme, the NOMA power allocation parameter (NPAP), and the interference temperature limit (ITL) apportioning parameter (ITLAP) depend on channel statistics. The third adaptation (presented for the first time in literature) used in two other proposed schemes involves selection of inter-dependent NPAP and ITLAP based on channel state information (CSI). The fourth adaptation used in the third proposed scheme relates to use of CSI-dependent ITL, which is shown to dramatically improve performance. Optimum choices of NPAP and ITLAP are expressed in closed-form for all three schemes, and performance with these is analyzed (and validated by computer simulations) assuming imperfect successive interference cancellation and residual self-interference cancellation at the NU.

Automated summary

In this paper, the importance of intelligent adaptation in underlay cooperative non-orthogonal multiple access (CNOMA) is demonstrated. The first adaptation involves switching between the cooperative mode (CM) and the non-cooperative mode (NCM), while the second adaptation is related to transmit antenna selection. The third adaptation, presented for the first time, involves the selection of inter-dependent parameters based on channel state information (CSI), and the fourth adaptation is the use of CSI-dependent interference temperature limit (ITL) to improve performance.