Muhammad Shoaib Bin Altaf

Outline Motivation Actual Flow Optimizations Approach Results Conclusion

Motivation Convolutional coding with Viterbi decoding a powerful method for FEC in Communication Systems Viterbi Algorithm is based on Maximum Likelihood Estimation which is sequential. Thus slow. Modern Communications Standards like Wimax support very high throughput Data speed is increasing so is the need for high speed Viterbi decoding We are looking for such a scheme which gives vectorized output bits

Actual Algorithmic Flow We have done this stuff in our Homework as well On building trellis, at each stage path metric will be computed Best path metric computation at each stage Traceback decoding done bit by bit Each clock cycle, one bit will be decoded

Optimization VA is sequential but the “Good” thing is, it’s Recursive Various optimization possibilities can be employed for speed-up. Since the purpose was to have vectorized output, the only viable option is ‘Look Ahead Transformation’ Discussed Look Ahead transformation for Hoffman decoding in the class Block processing of the data

Optimization Contd. Decoding using 2 Look Ahead step.

Optimization Contd. Increasing the number of Look Ahead steps

Optimization Contd. Instead of 2 paths, we have to select the minimum among the 4 possible paths Lookup table needs to be changed

Approach Matlab Simulation N= 10^5 bits of data Two implementations of VA Constraint Length K= 3 One based on simple decoding Other based on Look Ahead Transformation Performance comparison to justify the correctness of the suggested approach

Results Data processing speed nearly doubles on taking a single Look Ahead step. Sequential VAOptimized VA Execution time in Seconds

Results Contd.. Performance Comaprsion

Conclusion Look Ahead Transformation is very attractive for increasing the throughput for Recursive Algorithms No loss in decoding abilities Depending on the Application Look Ahead step can be increased to any value The extra hardware cost is nominal as compared to the achieved performance In this Project the main focus was on speeding up the decoding rate irrespective of the extra hardware cost incurred