CREST-CRCN Seminar

Cognitive Radio and Dynamic Spectrum Management in Wireless Communications
by Dr. Sunil Maharaj, SENTECH Chair in Broadband Wireless Multimedia Communications
2015-03-12, 04:00 PM in NSB 150

Abstract

Cognitive radio (CR) has been proposed as a technology that is able to make efficient usage of the radio frequency

spectrum through opportunistic and dynamic spectrum access. CRs rely on a process, known as spectrum sensing (SS),

to gather information about the radio environment in which they wish to operate. This information allows them to

make use of appropriate spectrum resources and also helps them to avoid interference with other users of the spectrum.

However, the accuracy of this information is of paramount importance since inaccurate data could negatively impact

upon the performance of a CR network (CRN). One of the problems associated with SS is the hidden node problem,

where due to severe shadowing or multipath fading, it is often not possible for a single sensing node to obtain accurate

results. Cooperation between multiple sensing nodes may thus be employed to obtain more accurate SS decisions.

Energy efficiency in cognitive radio networks (CRN) is of paramount importance since secondary users (SU) are often

likely to be energy constrained. While spectrum sensing (SS) is a critical CRN function, repetitive SS events can

significantly reduce the battery life of sensing devices. However, energy efficiency can be improved by employing

spectrum opportunity forecasting (SOF) and optimal scheduling for sensor node activation to reduce the required

number of SS events. In this presentation, a combination of SOF and optimal scheduling is thus explored. The

application of SOF to cooperative SS is one of the unique contributions we have undertaken. Results indicated that this

combination could significantly reduce sensor node energy consumption and in so doing increase CRN lifetime. The

presentation will also cover the Spectrum Sensing measurement campaign done in South Africa and the opportunities

in TVWS for future wireless communications such as for Rural Communications using Dynamic Spectrum

Management for Long Range Wi-Fi Rural Broadband.

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