Interference aware wireless networks with point to point beamforming
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Recent dramatic changes in the end-user devices and applications demand the idea of peer-peer packet transmissions without the help of base stations or wire-line backbone networks. This concept of distributed communication systems has quite a few areas of interest, whether it is gaming, emergency response, or for surveying purposes. Network scientists now are more interested in this de-centralized Ad-Hoc Network than the conventional centralized base-station or wire line based communication system. Very little research has been done in simulating the beamforming procedure and actually studying the effects of change in beam width of the antenna pattern and some other antenna parameters. In our work we investigate and build a model that could possibly overcome interference by changing such physical layer parameters and using them to exploit the benefits not only in the physical layer but also in network and medium access layers. In particular we delve into the physical antenna parameters like beamwidth, main lobe gain, and we see how it affects the network capacity. We intend to investigate power calculations around a transceiver and build a model that will provide an estimate of interference severity for medium access purposes. We then use this model to show the enhancement in network efficiency from conventional omnidirectional and directional cases for different main lobe gains. The interference model presented in this study has been simulated in MATLAB and studied extensively for the efficiency and capacity of the network with varying parameters namely beam width, network area, and number of users. With the help of simulations and analysis of the results we conclude that the beamwidth and power calculations play a major role in enhancing the network capacity. The results for our beamforming model show the enhancement in network efficiency from conventional omni-directional and directional cases.
Table of Contents
Introduction -- Beamforming -- Network model -- Interference model -- Simulation -- Conclusions and future work