This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state...This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state information(CSI).Based on reasonable assumptions and approximations,we derive the effective capacity as a function of the pilot length,decoding error probability,transmit power and the sub-channel number.Then we reveal significant impact of the above parameters on the effective capacity.A closed-form lower bound of the effective capacity is derived and an alternating optimization based algorithm is proposed to find the optimal pilot length and decoding error probability.Simulation results validate our theoretical analysis and show that the closedform lower bound is very tight.In addition,through the simulations of the optimized effective capacity,insights for pilot length and decoding error probability optimization are provided to evaluate the optimal parameters in realistic systems.展开更多
With the rapid development of smart terminals and infrastructures,as well as diversified applications(e.g.,autonomous driving,virtual and augmented reality,space-air-ground integrated networks)with colorful demands,cu...With the rapid development of smart terminals and infrastructures,as well as diversified applications(e.g.,autonomous driving,virtual and augmented reality,space-air-ground integrated networks)with colorful demands,current networks(e.g.,4G and 5G networks)may not be well suited to the requirements of novel applications and services.Recently,efforts from both the industry and academia have been made on the research into 6G networks,artificial intelligence(AI)will play a pivotal role in the design and optimization of 6G networks.展开更多
基金supported by the National Natural Science Foundation of China under grant 61941106。
文摘This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state information(CSI).Based on reasonable assumptions and approximations,we derive the effective capacity as a function of the pilot length,decoding error probability,transmit power and the sub-channel number.Then we reveal significant impact of the above parameters on the effective capacity.A closed-form lower bound of the effective capacity is derived and an alternating optimization based algorithm is proposed to find the optimal pilot length and decoding error probability.Simulation results validate our theoretical analysis and show that the closedform lower bound is very tight.In addition,through the simulations of the optimized effective capacity,insights for pilot length and decoding error probability optimization are provided to evaluate the optimal parameters in realistic systems.
文摘With the rapid development of smart terminals and infrastructures,as well as diversified applications(e.g.,autonomous driving,virtual and augmented reality,space-air-ground integrated networks)with colorful demands,current networks(e.g.,4G and 5G networks)may not be well suited to the requirements of novel applications and services.Recently,efforts from both the industry and academia have been made on the research into 6G networks,artificial intelligence(AI)will play a pivotal role in the design and optimization of 6G networks.
