Exploiting Spatial and Temporal Correlations for Signal-Centric Predictive Medium Access Control in M2M Communication Networks

• Main Authors: Kuo, Fu-Ta, 郭阜達
• Other Authors: Gau, Rung-Hung
• Format: Others
• Language: en_US
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/6483m3

碩士 === 國立交通大學 === 電信工程研究所 === 103 === In this thesis, we propose spatial and temporal correlations for signal-centric predictive polling for medium access control in the machine-to-machine communication networks. Due to the lots of MTC devices and the limited resource for medium access control, it is not feasible for all machines to send data successfully in one time slot. Many previous works on medium access control do not take into consideration of the values of the signal. The proposed signal-centric predictive polling schemes always collect the most valuable signal. We construct the model by using autoregressive model to calculate the mean squared error (MSE) of prediction, and exploit the statistical correlations of regular processes and the characteristics of the spatial relation on M2M communication network. We adopt the widely used autoregressive (AR) model to calculate the mean squared error (MSE) of prediction based on the polling decision. We formulate a discrete optimization problem to make the optimal polling decision in one time slot, and justify the proposed algorithm by simulation to show our algorithm could significantly outperform the round-robin scheme and temporal correlation for signal-centric predictive polling algorithm.