We consider an image semantic communication system in a time-varying fading Gaussian MIMO channel,with a finite number of channel states.A deep learning-aided broadcast approach scheme is proposed to benefit the adapt...We consider an image semantic communication system in a time-varying fading Gaussian MIMO channel,with a finite number of channel states.A deep learning-aided broadcast approach scheme is proposed to benefit the adaptive semantic transmission in terms of different channel states.We combine the classic broadcast approach with the image transformer to implement this adaptive joint source and channel coding(JSCC)scheme.Specifically,we utilize the neural network(NN)to jointly optimize the hierarchical image compression and superposition code mapping within this scheme.The learned transformers and codebooks allow recovering of the image with an adaptive quality and low error rate at the receiver side,in each channel state.The simulation results exhibit our proposed scheme can dynamically adapt the coding to the current channel state and outperform some existing intelligent schemes with the fixed coding block.展开更多
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
To meet the high-performance requirements of fifth-generation(5G)and sixth-generation(6G)wireless networks,in particular,ultra-reliable and low-latency communication(URLLC)is considered to be one of the most important...To meet the high-performance requirements of fifth-generation(5G)and sixth-generation(6G)wireless networks,in particular,ultra-reliable and low-latency communication(URLLC)is considered to be one of the most important communication scenarios in a wireless network.In this paper,we consider the effects of the Rician fading channel on the performance of cooperative device-to-device(D2D)communication with URLLC.For better performance,we maximize and examine the system’s minimal rate of D2D communication.Due to the interference in D2D communication,the problem of maximizing the minimum rate becomes non-convex and difficult to solve.To solve this problem,a learning-to-optimize-based algorithm is proposed to find the optimal power allocation.The conventional branch and bound(BB)algorithm are used to learn the optimal pruning policy with supervised learning.Ensemble learning is used to train the multiple classifiers.To address the imbalanced problem,we used the supervised undersampling technique.Comparisons are made with the conventional BB algorithm and the heuristic algorithm.The outcome of the simulation demonstrates a notable performance improvement in power consumption.The proposed algorithm has significantly low computational complexity and runs faster as compared to the conventional BB algorithm and a heuristic algorithm.展开更多
The additional diversity gain provided by the relays improves the secrecy capacity of communications system significantly. The multiple hops in the relaying system is an important technique to improve this diversity g...The additional diversity gain provided by the relays improves the secrecy capacity of communications system significantly. The multiple hops in the relaying system is an important technique to improve this diversity gain. The development of an analytical mathematical model of ensuring security in multicasting through fading channels incorporating this benefit of multi-hop relaying is still an open problem. Motivated by this issue, this paper considers a secure wireless multicasting scenario employing multi-hop relaying technique over frequency selective Nakagami-m fading channel and develops an analytical mathematical model to ensure the security against multiple eavesdroppers. This mathematical model has been developed based on the closed-form analytical expressions of the probability of non-zero secrecy multicast capacity (PNSMC) and the secure outage probability for multicasting (SOPM) to ensure the security in the presence of multiple eavesdroppers. Moreover, the effects of the fading parameter of multicast channel, the number of hops and eavesdropper are investigated. The results show that the security in multicasting through Nakagami-m fading channel with multi-hop relaying system is more sensitive to the number of hops and eavesdroppers. The fading of multicast channel helps to improve the secrecy multicast capacity and is not the enemy of security in multicasting.展开更多
基金supported in part by the National Key R&D Project of China under Grant 2020YFA0712300National Natural Science Foundation of China under Grant NSFC-62231022,12031011supported in part by the NSF of China under Grant 62125108。
文摘We consider an image semantic communication system in a time-varying fading Gaussian MIMO channel,with a finite number of channel states.A deep learning-aided broadcast approach scheme is proposed to benefit the adaptive semantic transmission in terms of different channel states.We combine the classic broadcast approach with the image transformer to implement this adaptive joint source and channel coding(JSCC)scheme.Specifically,we utilize the neural network(NN)to jointly optimize the hierarchical image compression and superposition code mapping within this scheme.The learned transformers and codebooks allow recovering of the image with an adaptive quality and low error rate at the receiver side,in each channel state.The simulation results exhibit our proposed scheme can dynamically adapt the coding to the current channel state and outperform some existing intelligent schemes with the fixed coding block.
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.
基金supported in part by the National Natural Science Foundation of China under Grant 61771410in part by the Sichuan Science and Technology Program 2023NSFSC1373in part by Postgraduate Innovation Fund Project of SWUST 23zx7101.
文摘To meet the high-performance requirements of fifth-generation(5G)and sixth-generation(6G)wireless networks,in particular,ultra-reliable and low-latency communication(URLLC)is considered to be one of the most important communication scenarios in a wireless network.In this paper,we consider the effects of the Rician fading channel on the performance of cooperative device-to-device(D2D)communication with URLLC.For better performance,we maximize and examine the system’s minimal rate of D2D communication.Due to the interference in D2D communication,the problem of maximizing the minimum rate becomes non-convex and difficult to solve.To solve this problem,a learning-to-optimize-based algorithm is proposed to find the optimal power allocation.The conventional branch and bound(BB)algorithm are used to learn the optimal pruning policy with supervised learning.Ensemble learning is used to train the multiple classifiers.To address the imbalanced problem,we used the supervised undersampling technique.Comparisons are made with the conventional BB algorithm and the heuristic algorithm.The outcome of the simulation demonstrates a notable performance improvement in power consumption.The proposed algorithm has significantly low computational complexity and runs faster as compared to the conventional BB algorithm and a heuristic algorithm.
文摘The additional diversity gain provided by the relays improves the secrecy capacity of communications system significantly. The multiple hops in the relaying system is an important technique to improve this diversity gain. The development of an analytical mathematical model of ensuring security in multicasting through fading channels incorporating this benefit of multi-hop relaying is still an open problem. Motivated by this issue, this paper considers a secure wireless multicasting scenario employing multi-hop relaying technique over frequency selective Nakagami-m fading channel and develops an analytical mathematical model to ensure the security against multiple eavesdroppers. This mathematical model has been developed based on the closed-form analytical expressions of the probability of non-zero secrecy multicast capacity (PNSMC) and the secure outage probability for multicasting (SOPM) to ensure the security in the presence of multiple eavesdroppers. Moreover, the effects of the fading parameter of multicast channel, the number of hops and eavesdropper are investigated. The results show that the security in multicasting through Nakagami-m fading channel with multi-hop relaying system is more sensitive to the number of hops and eavesdroppers. The fading of multicast channel helps to improve the secrecy multicast capacity and is not the enemy of security in multicasting.
