A New Leakage-Based Precoding Scheme in IoT Oriented Cognitive MIMO-OFDM Systems

This paper considers physical layer interference management and network capacity improvement in Internet of Things (IoT)-oriented cognitive MIMO-OFDM systems, where the IoT devices access to the licensed spectrum by cognitive radio in spectrum underlay. Aiming to fully eliminate the interference to primary user as well as ensuring optimal QoS for all the cognitive IoT devices, in this paper, we propose a leakage-based precoding scheme with dimensionality reduction and SLNR criterion. More specifically, we first introduce a new channel estimation method using the multi-channel ratio algorithm that requires no feedback from the primary network. Second, with the estimated interference channel, we eliminate the interference to the primary user by a low complexity subspace projection with dimensionality reduction. Finally, by fully exploiting the generalized Rayleigh quotient, we propose the leakage-based precoding scheme that aims to optimize both the leakage power and noise power of the IoT devices. Theoretical and numerical results demonstrate that the proposed leakage-based precoding scheme can satisfy the low-cost and self-organized features of IoT networks, and achieves significant improvements on bit error rate performance and network capacity while causing no interference to the primary user.