Catalyzing Random Access at Physical Layer for Internet of Things:An Intelligence Enabled User Signature Code Acquisition Approach  

作　　者：Xiaojie Fang Xinyu Yin Xuejun Sha Jinghui Qiu Hongli Zhang 

机构地区：[1]School of Electronic and Information Engineering,Harbin Institute of Technology,Harbin 1500001,China [2]Science and Technology on Communication Networks Laboratory,Shijiazhuang 050050,China [3]School of Computer Science and Technology,Harbin Institute of Technology,Harbin 150001,China

出　　处：《China Communications》2021年第10期181-192,共12页中国通信（英文版）

基　　金：supported in part by Natural Science Foundation of Heilongjiang Province of China under Grant YQ2021F003;in part by the National Natural Science Foundation of China under Grant 61901140;in part by China Postdoctoral Science Foundation Funded Project under Grant 2019M650067;in part by Science and Technology on Communication Networks Laboratory under Grant SCX21641X003。

摘　　要：Exploiting random access for the underlying connectivity provisioning has great potential to incorporate massive machine-type communication(MTC)devices in an Internet of Things(Io T)network.However,massive access attempts from versatile MTC devices may bring congestion to the IIo T network,thereby hindering service increasing of IIo T applications.In this paper,an intelligence enabled physical(PHY-)layer user signature code acquisition(USCA)algorithm is proposed to overcome the random access congestion problem with reduced signaling and control overhead.In the proposed scheme,the detector aims at approximating the optimal observation on both active user detection and user data reception by iteratively learning and predicting the convergence of the user signature codes that are in active.The crossentropy based low-complexity iterative updating rule is present to guarantee that the proposed USCA algorithm is computational feasible.A closed-form bit error rate(BER)performance analysis is carried out to show the efficiency of the proposed intelligence USCA algorithm.Simulation results confirm that the proposed USCA algorithm provides an inherent tradeoff between performance and complexity and allows the detector achieves an approximate optimal performance with a reasonable computational complexity.

关 键 词：Internet of Things(IoT) artificial intelligence physical layer CROSS-ENTROPY random access 

分 类 号：TP391.44[自动化与计算机技术—计算机应用技术] TN929.5[自动化与计算机技术—计算机科学与技术]