Error Control Coding for Performance Improvement
Meeting Challenges in Cognitive Radio
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Claude Shannon, the father of Information Theory, in 1948 showed that every noisy channel has associated with it an information capacity C bits/second, below which it is possible to encode messages (by representing them as long binary strings) such that they can be received and decoded with arbitrarily low probability of error. His proof of the capacity theorem showed that for transmission rates below C bits/second the error probability averaged over all randomly selected codes can be made as small as desired. While this implies the existence of good codes, it left open the problem of designin...
Claude Shannon, the father of Information Theory, in 1948 showed that every noisy channel has associated with it an information capacity C bits/second, below which it is possible to encode messages (by representing them as long binary strings) such that they can be received and decoded with arbitrarily low probability of error. His proof of the capacity theorem showed that for transmission rates below C bits/second the error probability averaged over all randomly selected codes can be made as small as desired. While this implies the existence of good codes, it left open the problem of designing such codes. Since then till today, error control coding has registered continuous and noteworthy progress, yet the doors opened up by Shannon are still wide open. The reason is the increased demand on C , which is many folds greater than what Shannon and his team had expected.Heading towards the Cognitive Technology, wherein Bandwidth (BW) allocation is dynamic one has to configure the entire transceiver system to work over the available BW. The book focuses on how to optimize the BER (Bit error rate) performance of codec. Applications worked on include those in great demand;Mobile & WiMax
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