Abstract This paper discusses an artificial noise‐aided intelligent reflecting surface‐MIMO–OFDM system physical layer secure communication, in which two cases for the intelligent reflecting surface reflection coefficient models are considered separately, that is unit modulus constraint for the reflection coefficients and the more practical situation of amplitude phase‐shift dependence. Then the problem of joint optimisation for the precoding matrix, artificial noise covariance matrix and intelligent reflecting surface reflection coefficient matrix to maximise the sum secrecy rate under the power constraint at the transmitter is formulated, and then an alternate optimisation‐based inexact block coordinate descent algorithm is proposed to tackle the formulated non‐convexity problem. For the problem with unit modulus constraint for the intelligent reflecting surface reflection coefficients, closed‐form solutions of the optimisation variables are obtained by utilising the Lagrange multiplier method and the complex circular manifold method. For the problem with intelligent reflecting surface reflection coefficient amplitude phase‐shift dependence, alternate optimisation‐based penalty method is used to obtain the intelligent reflecting surface optimal reflection matrix. Numerical results indicate that the algorithm for the intelligent reflecting surface reflection coefficient unit modulus constraint achieves the maximum secrecy rate, and the algorithm for the intelligent reflecting surface reflection coefficient of amplitude phase‐shift dependence has the sub‐optimal performance, and the benchmark schemes such as no intelligent reflecting surface and intelligent reflecting surface random phase shift strategies have the worst and similar performance.

Cognitive radio is introduced into the demand response management (DRM) of smart grid with the hope of alleviating the shortage of spectrum resources and improving communication quality. In this paper, we adopt an energy detection algorithm based on generalized stochastic resonance (GSRED) to improve the spectrum sensing accuracy under the circumstances of low signal-to-noise ratio without increasing system overhead. Specifically, a DRM scheme based on real-time pricing is investigated, and the social welfare is taken as the main index to measure system control performance. Furthermore, considering the adverse effects incurred by incorrect spectrum sensing, we incorporate the probability of the DRM system causing interference to primary user and spectrum loss rate into the evaluation index of the system control performance and give the final expression of the global optimization problem. The influence of sensing time on system communication outage probability and spectrum loss rate is elaborated in detail through theoretical derivation and simulation analysis. Simulation results show that the GSRED algorithm has higher detection probability under the same conditions compared with the traditional energy detection algorithm, thus guaranteeing lower communication outage probability and spectrum loss rate.

The huge demand and growth of high-speed mobile data applications drive the development of the next generation wireless systems. A very significant evolution of mobile telecommunication technologies is the introduction of the high-speed downlink shared channel used by many users to efficiently accommodate packet data in networks. In a wireless environment, because of the time-varying channel fluctuations of wireless links, efficient use of the large available bandwidth cannot be achieved without adopting sophisticated channel-state-aware packet scheduling strategies. This article presents a novel scheduling algorithm to provide very high-data-rate downstream access in wireless network and evaluate the basic performance by carrying out simulation. The proposed scheme can effectively improve system performance in terms of throughput and fair share of the system resources and provide high-speed connections with channel-aware radio resource allocation.