Pruning of Blind Decoding Results for Long Term Evolution

Long Term Evolution (LTE) downlink sub frame includes two major physical channels. One is a physical downlink control channel (PDCCH) and the other is a physical downlink shared channel (PDSCH). In Long-Term Evolution (LTE) downlink control channel, a large number of blind decoding attempts are made, while the number of valid code words is limited. The blind decoding results are then verified using a 16-bit cyclic redundancy check (CRC). However, even with the 16-bit CRC, the false alarm (FA) rate of such blind decoding is inevitably high. This paper investigates the problem of pruning of blind decoding results for reduction of the FA rate. To the best of our knowledge, the approach using a soft correlation metric (SCM) shows the best FA reduction performance among existing schemes. However, following the Bayes principle, we propose novel likelihood-based pruning that provides systematic balancing between the FA rate and the miss (MS) rate.