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Resource Allocation for mMTC/H2H Coexistence with H2H’s Success Probability of Data Transmission

机译:mMTC / H2H的资源分配与H2H数据传输成功的可能性共存

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To accommodate massive machine-type communication (mMTC) in the networks originally designed for human-to-human (H2H) communication, we investigate the resource allocation for the mMTC/H2H coexisting network where the conventional random access (RA) and data transmission procedures are tailored for mMTC. The resource allocation strategy jointly consider the resource allocation of physical random access channel (PRACH) and physical uplink shared channel (PUSCH), aiming to support more MTC users while protecting the quality-of-service (QoS) of traditional H2H communication. A Markov chain is utilized to explicitly model the RA and data transmissions of H2H, and H2H’s success probability of data transmission is derived under the analysis of stationary distribution. Then, we formulate a nonlinear integer programming (NLIP) problem which aims to maximize MTC throughput while guaranteeing H2H’s success probability of data transmission. By solving the optimization problem with a modified particle swarm optimization method, we obtain the resource allocation strategy that achieves a balance between PRACH and PUSCH in terms of resource efficiency. Simulation results demonstrate the superiority of our proposed resource allocation strategy over traditional LTE strategy in the scenario of mMTC/H2H coexistence.
机译:为了在最初设计用于人对人(H2H)通信的网络中容纳大规模机器类型通信(mMTC),我们研究了mMTC / H2H共存网络的资源分配,其中常规随机访问(RA)和数据传输过程为mMTC量身定制。资源分配策略共同考虑了物理随机接入信道(PRACH)和物理上行链路共享信道(PUSCH)的资源分配,旨在支持更多的MTC用户,同时保护传统H2H通信的服务质量(QoS)。利用马尔可夫链对H2H的RA和数据传输进行显式建模,并通过对平稳分布的分析得出H2H数据传输的成功概率。然后,我们提出了一个非线性整数规划(NLIP)问题,目的是在保证H2H数据传输成功概率的同时最大化MTC吞吐量。通过使用改进的粒子群优化方法解决优化问题,我们获得了在资源效率方面实现PRACH和PUSCH之间平衡的资源分配策略。仿真结果表明,在mMTC / H2H共存的情况下,我们提出的资源分配策略优于传统的LTE策略。

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