Intelligent Reflecting Surface Aided NOMA-HARQ Based IoT Framework for Future Wireless Networks

In sixth-generation (6G) wireless networks, non-orthogonal multiple access (NOMA) technology is widely used to improve the spectrum efficiency. Along with NOMA, hybrid automatic repeat request (HARQ) technique is used to enhance the reliability of communication system. Recently, intelligent reflecting surfaces (IRS) are a futuristic transmission technology that can achieve high spectral and energy efficiency at low cost. In this paper, an IRS aided downlink NOMA-HARQ based Internet of Things (IoT) framework is proposed to enhance the IoT devices' performance in non-line-of-sight (NLoS) region. Further, to enhance the performance of NLoS IoT device/users, two NOMA-HARQ aided IRS schemes are proposed namely: NOMA-selection combining (SC) with IRS and NOMA-maximum ratio combining (MRC) with IRS. This paper formulates and examines the IoT user/device performance in terms of the achievable data rates, outage probability, bit error rate (BER) and diversity order in IRS aided downlink NOMA-HARQ environment with variable signal-to-noise ratio (SNR). With the help of the simulation results, it is demonstrated that in dynamic wireless channels, the proposed schemes outperform the conventional NOMA with HARQ (NOMA-HARQ) in terms of achievable data rates, outage probability, BER and diversity order.