Blind Recognition of Parameters of Reed Solomon Code from Intercepted Erroneous Codewords

Error correcting codes are designed for reliable transmission of digital information over a noisy channel. Several papers have been published on blind identification of binary FEC codes but papers reported on the identification of non-binary error correcting codes are less. Due to its strong error correction capability, RS (Reed-Solomon) code is being used widely. So technique for blind recognition of RS code is required to analyse intercepted signal as well as for intelligent communication. This paper presents a technique for extraction of parameters of Reed-Solomon code from intercepted demodulated bitstream. The proposed algorithm is very simple and hence it is very practical for hardware implementation. Our approach has been verified using MATLAB simulation

New Coding/Decoding Techniques for Wireless Communication Systems

Wireless communication encompasses cellular telephony systems (mobile communication), wireless sensor networks, satellite communication systems and many other applications. Studies relevant to wireless communication deal with maintaining reliable and efficient exchange of information between the transmitter and receiver over a wireless channel. The most practical approach to facilitate reliable communication is using channel coding. In this dissertation we propose novel coding and decoding approaches for practical wireless systems. These approaches include variable-rate convolutional encoder, modified turbo decoder for local content in Single-Frequency Networks, and blind encoder parameter estimation for turbo codes. On the other hand, energy efficiency is major performance issue in wireless sensor networks. In this dissertation, we propose a novel hexagonal-tessellation based clustering and cluster-head selection scheme to maximize the lifetime of a wireless sensor network. For each proposed approach, the system performance evaluation is also provided. In this dissertation the reliability performance is expressed in terms of bit-error-rate (BER), and the energy efficiency is expressed in terms of network lifetime