Abstract
Deploying a massive number of MTC (Machine - Type - Communication) devices in the current cellular mobile networks represents a great challenge as they may cause congestion and system overload for both RAN (Radio Access Network) and CN (Core Network) parts. To address this issue, we propose a novel algorithm, named Multi-Channel Slotted ALOHA-Optimal Estimation (MCSA-OE), which estimates the network status (the number of active devices), and thus better controlling the RAN access. Unlike most existing methods that consider only one channel, MCSA-OE uses the statistics of all the channels in order to estimate the number of arrivals (UE and MTC devices) in each RA (Random Access) slot. Simulation results demonstrate that MCSA-OE well tracks the number of arrivals as long as they are smaller than ln(RR), where R is the number of channels. Moreover, we propose to use MCSA-OE estimation to dynamically adjust the acbBarringFactor of the Access Class Barring (ACB) mechanism. Again, simulation results show that the behavior of our proposition merely tends to that of the best acknowledgment case, i.e. when the number of arrivals in each RA slot is well known.
Published Version
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