Compressed Sensing Channel Estimation for LTE-V

Abstract:

The evolution of the LTE standard withRelease-14has introduced several changes in the physical layer with a goal of catering to the needs of Intelligent Transportation Systems (ITS). Some of the changes include the use of SC-FDMA, a modified pilot pattern and improved scheduling. Typical vehicular environments are characterized by a multipath channel that is temporally varying. Such a channel affects the performance of an underlying SC-FDMA system by introducingInter-Carrier Interference(ICI). Additionally, the channel characteristics are dynamic, resulting in heterogeneous channel conditions with varying degrees of mobility. Channel estimation and equalization schemes are indispensable in overcoming the adverse ramifications of the channel by precisely parameterizing the channel through computationally feasible means. Here, an optimized channel characterization scheme that involves theRake-Matching Pursuit(RMP) algorithm for the estimation of the so called doubly selective channels and theLeast Squares(LS) scheme in low mobility conditions is suggested. A simple and low complex cognitive framework based on theIndex of Dispersionis also proposed to switch between the two schemes based on channel conditions. By virtue of its merits, the proposed channel estimation scheme provides good results in heterogeneous channel conditions and with a complexity that remains relevant for consumer hardware. Finally, an evaluation platform in Matlab®that is LTE standard compliant is made available to the research community. (LTE Evaluation Platform: https://git.nt.uni-saarland.de/HiMo/SimTool_LTE.) It includes the proposed schemes for channel estimation along with the cognitive framework.