Sparse Index OFDM Modulation for IoT Communications

Abstract

One of the greatest challenges facing the physical layer design of the internet of things (IoT) resides in the imposed constraint of very low power consumption. Recently, new modulation scheme termed OFDM with sparse index modulation (OFDM-SIM) has been introduced as an energy efficient multicarrier scheme (MCS). Although of its high energy efficiency (EE) and spectral efficiency (SE), OFDM-SIM cannot fulfill the IoT energy requirements owing to its high PAPR. In this regard, an enhanced OFDM-SIM is proposed in this paper as an energy efficient MCS for IoT communications. In particular, a novel clipping-compressive sensing (CS) based PAPR reduction technique for OFDM-SIM is proposed. In the transmitter (TX) side, considering the complexity constraints for IoT devices, the simple and low complex clipping method is exploited to deal with the PAPR issue. On the receiver (RX) side, a robust CS signal recovery scheme is proposed to deal with tough resulting clipping noise. Unlike high complex conventional CS-based schemes, the proposed scheme exploits the inherent sparsity of the received enhanced OFDM-SIM signal rather than clipping noise sparsity to achieve a low complex CS signal detection. Moreover, in this paper, the information-theoretic limits on sparsity recovery are exploited to derive an upper bound measure of the bit error rate (BER). The simulation results demonstrate the superiority of the proposed scheme, as it significantly enhances the overall system performance in terms of EE and PAPR reduction compared to the conventional clipped coded-OFDM.

Keywords

• IoT
• OFDM-sparse index modulation (OFDM-SIM)
• PAPR
• clipping
• compressive sensing (CS)