Relaying Threshold Based Random Access and Data Transmission Scheme for Grouped Massive MTC Networks

In this paper, we propose a relaying threshold based random access and data transmission scheme for grouped massive machine-type communications (mMTC)networks. Specifically, by employing the MTC gateways (MTCG), MTC devices (MTCD)are divided into groups. Radio resources are partitioned into 2 parts and then allocated to 2 links, respectively. In link 1, MTCDs transmit data packets to the associated MTCG through allocated orthogonal channels. Afterwards, MTCGs, whose buffer occupancy reaches the relaying threshold, access to the base station (BS)by contention-based random access procedure. Then, the successfully accessed MTCGs froward aggregated data packets to BS via assigned channels in link 2. To further optimize the performance of the proposed system, we adopt the Markov theory to analyze the state transition probability matrix of each MTCG's buffer occupancy, and then formulate the throughput maximization problem subject to the constraints on the resource partitioning ratio, relaying threshold of MTCG and stationary distribution of Markov chain. Moreover, by using the developed differential evolution (DE)based resource allocation algorithm, we efficiently solve the optimization problem. Simulation results show that our proposed scheme can efficiently improve the network performance as compared with the existing schemes.