Uniquely Decomposable Constellation Group-Based Sparse Vector Coding for Short Packet Communications

Sparse vector coding(SVC)is emerging as a potential technology for short packet communications.To further improve the block error rate(BLER)performance,a uniquely decomposable constellation group-based SVC(UDCG-SVC)is proposed in this article.Additionally,in order to achieve an optimal BLER performance of UDCG-SVC,a problem to optimize the coding gain of UDCG-based superimposed constellation is formulated.Given the energy of rotation constellations in UDCG,this problem is solved by converting it into finding the maximized minimum Euclidean distance of the superimposed constellation.Simulation results demonstrate the validness of our derivation.We also find that the proposed UDCGSVC has better BLER performance compared to other SVC schemes,especially under the high order modulation scenarios.

Minimizing Age of Information in the Uplink Multi-User Networks via Dynamic Bandwidth Allocation

Improving the information freshness is critical for the monitoring and controlling applications in the cellular Internet of Things(IoT).In this paper,we are interested in optimizing the bandwidth allocation dynamically to improve the information freshness of the short packet based uplink status updates,which is characterized by a recently proposed metric,age of information(Ao I).We first design a status update scheme with channel distribution information(CDI).By relaxing the hard bandwidth constraint and introducing a Lagrangian multiplier,we first decouple the multi-MTCD bandwidth allocation problem into a single MTCD Markov decision process(MDP).Under the MDP framework,after variable substitution,we obtain the single-MTCD status update scheme by solving a linear programming problem.Then,we adjust the Lagrangian multiplier to make the obtained scheme satisfy the relaxed bandwidth constraint.Finally,a greedy policy is built on the proposed scheme to adjust the bandwidth allocation in each slot to satisfy the hard bandwidth constraint.In the unknown environment without CDI,we further design a bandwidth allocation scheme which only maximizes the expected sum Ao I drop within each time slot.Simulation results show that in terms of AoI,the proposed schemes outperform the benchmark schemes.

Power optimization for multiple QoS,delay,and BER classes relying on nite-delay information theory

Future communication systems will include di erent types of messages requiring di erent transmission rates,packet lengths,and service qualities.We address the power-optimization issues of communication systems conveying multiple message types based on nite-delay information theory.Given both the normalized transmission rate and the packet length of a system,the actual residual decoding error rate is a function of the transmission power.We propose a generalized power allocation framework for multiple message types.Two di erent optimization cost functions are adopted:the number of service-quality violations encountered and the sum log ratio of the residual decoding error rate.We provide the optimal analytical solution for the former cost function and a heuristic solution based on a genetic algorithm for the latter one.Finally,the performance of the proposed solutions are evaluated numerically.