Recently, wireless communication industries have begun to extend their services to machine-type communication devices as well as to user equipments. Such machine-type communication devices as meters and sensors need intermittent uplink resources to report measured or sensed data to their serving data collector. It is however hard to dedicate limited uplink resources to each of them. Thus, efficient service of a tremendous number of devices with low activities may consider simple random access as a solution. The data collectors receiving the measured data from many sensors simultaneously can successfully decode only signals with signal-to-interference-plus-noise-ratio (SINR) above a certain value. The main design issues for this environment become how many data collectors are needed, how much power sensor nodes transmit with, and how wireless channels affect the performance. This paper provides answers to those questions through a stochastic analysis based on a spatial point process and on simulations. Index Terms-M2M, stochastic geometry, spatial reuse, outage probability, network design, Poisson point process.
By assuming PPP distributed sensors and data collectors, the distribution of the signal-to-interference-plus-noise ratio (SINR) at a data collector was identified in REF .
Random Deployment of Data Collectors for Serving Randomly-Located Sensors
IEEE Transactions on Wireless Communications
IEEE Transactions on Wireless Communications
Computer Science Mathematics