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In order for the unlicensed or secondary users to use the licensed spectrum cognitive radio has been proposed. The licensed frequencies can be made use of by unlicensed users through dynamic spectrum access so as to reduce spectrum scarcity. This requires intelligent spectrum sensing techniques. The detection of unused frequency bands is the most challenging task in cognitive radio. In this study such unused spectrum is predicted by exploring the primary users presence in minimum time using matched filter based detection incorporating optimal threshold selection, thereby increasing the sensing accuracy and interference reduction of secondary network.

Congestion in Wireless Sensor Networks (WSN) get worse when there are multiple and random flows of data in which some have superior significance over the others requiring fidelity in terms of packet delivery, QoS, energy efficiency and throughput. In node-level, congestion leads to impairment of packets that obviously reduces the QoS. In this paper, we present a Cluster based congestion control with Rate Adjustment based on Priority (CRAP) protocol, which self-organizes the sensor nodes into clusters. These clusters monitor congestion in a proactive manner within its confined range which exchanges information among them and adjusts the traffic rate when one cluster has high priority flow over the other. This rate adjustment is based on the exchange of traffic rate estimate among the clusters that reduces packet re-transmissions and energy loss. Our simulation expedites system wide rate control resulting in good throughput, very low packet loss probability and delay that deals with multiple, random flows of data.

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