为解决海量机器类通信(mMTC,massive machine type communications)场景下,机器类通信设备(MTCD,machine type communication device)采用传统随机接入方案时,往往出现网络严重拥塞,导致大量MTCD无法成功接入网络问题,提出了一种基于前导码重传辅助的动态接入类别限制(PRT-ACB,preamble retransmission access class barring)方案。利用MTCD的前导码重传次数,将每个随机接入机会(RAO,random access opportunity)中尝试发起接入的MTCD划分为高、低优先级,结合每个RAO中负载数估计模型,分别为其设定随每个RAO中的接入负载动态变化的高、低优先级限制因子和可用前导码池,使更多MTCD能在未达到最大前导码传输次数前成功接入网络。仿真结果表明,所提方案能有效提升MTCD的接入成功概率,降低MTCD接入网络所需时延。所提方案可以作为缓解海量通信设备同时接入网络造成拥塞的一种解决方案。
As a popular distributed machine learning framework,wireless federated edge learning(FEEL)can keep original data local,while uploading model training updates to protect privacy and prevent data silos.However,since wireless channels are usually unreliable,there is no guarantee that the model updates uploaded by local devices are correct,thus greatly degrading the performance of the wireless FEEL.Conventional retransmission schemes designed for wireless systems generally aim to maximize the system throughput or minimize the packet error rate,which is not suitable for the FEEL system.A novel retransmission scheme is proposed for the FEEL system to make a tradeoff between model training accuracy and retransmission latency.In the proposed scheme,a retransmission device selection criterion is first designed based on the channel condition,the number of local data,and the importance of model updates.In addition,we design the air interface signaling under this retransmission scheme to facilitate the implementation of the proposed scheme in practical scenarios.Finally,the effectiveness of the proposed retransmission scheme is validated through simulation experiments.
Within the framework of the 5G new radio(NR),we propose a new hybrid automatic repeat request(HARQ)scheme to improve the throughput performance.The difference between the proposed scheme and the conventional one lies in the first retransmission,where the erroneous coded block group is interleaved and superimposed(XORed)onto a fresh coded block group.At the receiver,an iterative message-passing decoding algorithm can be employed to recover the target erroneous code block group(CBG).Only when the superposed retransmission fails,the conventional incremental redundancy(IR)or repetition redundancy(RR)retransmission is initiated.In any case,since the first retransmission is along with but has negligible effect on the fresh CBG,it costs neither transmitted power nor bandwidth.Monte-Carlo simulation results reveal that the presented HARQ schemes can achieve throughput improvements up to 10%over block fading channels and up to 50%over fast fading channels in comparison with the original 5G CBG-level HARQ scheme but without excessively increasing the implementation complexity.
