Interference Reduction Technique in Mobile Adhoc Networks using Mathematical Prediction Filters

Abstract

Interference is one of the major degrading factors of mobile ad hoc networks (MANET). Since, MANET transmits over the single wireless channel; packets of the same flow interfere with each other greatly. This mutual interference causes the bottleneck over the network. Further, predicting interference accurately around a transmitter or receiver is a complicated task. As a solution to these problems, in this paper, we propose an interference reduction technique for MANET using mathematical prediction filters. The technique used Hidden Markov Model (HMM) for predicting the interference of the nodes. Initial transmission power is set by comparing received signal power with minimum and maximum values. During data transmission, RTS and CTS messages are exchanged using initial transmission power level and they include interference value of the source and destination respectively. The source then uses the interference value of the destination to transmit data packet. On the other hand, the destination uses the interference value of the source for transmitting the acknowledgement (ACK) packet to the source. Thus, this interference calculation at both ends reduces the interference. By simulation, we show that our technique reduces the interference considerably.

Priority Based Optimized Backoff Algorithm for Collision Avoidance in Wireless Ad Hoc Networks

“…[20] [21]. There are lot interference reduction and mitigation techniques available in literature [22]. The Binary Exponential BO (BEB) algorithm provides relative priority among multiple traffic classes [4].…”