Active User and Data Detection for Uplink Grant-free NOMA Systems

This paper proposes some low complexity algorithms for active user detection(AUD),channel estimation(CE)and multi-user detection(MUD)in uplink non-orthogonal multiple access(NOMA)systems,including single-carrier and multi-carrier cases.In particular,we first propose a novel algorithm to estimate the active users and the channels for single-carrier based on complex alternating direction method of multipliers(ADMM),where fast decaying feature of non-zero components in sparse signal is considered.More importantly,the reliable estimated information is used for AUD,and the unreliable information will be further handled based on estimated symbol energy and total accurate or approximate number of active users.Then,the proposed algorithm for AUD in single-carrier model can be extended to multi-carrier case by exploiting the block sparse structure.Besides,we propose a low complexity MUD detection algorithm based on alternating minimization to estimate the active users’data,which avoids the Hessian matrix inverse.The convergence and the complexity of proposed algorithms are analyzed and discussed finally.Simulation results show that the proposed algorithms have better performance in terms of AUD,CE and MUD.Moreover,we can detect active users perfectly for multi-carrier NOMA system.

Exploiting blockchain for dependable services in zero-trust vehicular networks

The sixth-generation(6G)wireless communication system is envisioned be cable of providing highly dependable services by integrating with native reliable and trustworthy functionalities.Zero-trust vehicular networks is one of the typical scenarios for 6G dependable services.Under the technical framework of vehicle-and-roadside collaboration,more and more on-board devices and roadside infrastructures will communicate for information exchange.The reliability and security of the vehicle-and-roadside collaboration will directly affect the transportation safety.Considering a zero-trust vehicular environment,to prevent malicious vehicles from uploading false or invalid information,we propose a malicious vehicle identity disclosure approach based on the Shamir secret sharing scheme.Meanwhile,a two-layer consortium blockchain architecture and smart contracts are designed to protect the identity and privacy of benign vehicles as well as the security of their private data.After that,in order to improve the efficiency of vehicle identity disclosure,we present an inspection policy based on zero-sum game theory and a roadside unit incentive mechanism jointly using contract theory and subjective logic model.We verify the performance of the entire zero-trust solution through extensive simulation experiments.On the premise of protecting the vehicle privacy,our solution is demonstrated to significantly improve the reliability and security of 6G vehicular networks.