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Abstract-This letter deals with the problem of non data aided (NDA) signal to noise ratio (SNR) estimation of OFDM signals transmitted through unknown multipath fading channel. Most of existing OFDM SNR estimators are based on the knowledge of pilot sequences which is not applicable in some contexts such as cognitive radio for instance. We show that it is possible to take advantage of the periodic redundancy induced by the cyclic prefix to get an accurate NDA SNR estimator. Numerical simulations highlight the benefit of the proposed method compared with the state of the art.

International audienceThis paper addresses the problem of decoding in large scale MIMO systems. In this case, the optimal maximum likelihood detector becomes impractical due to an exponential increase of the complexity with the signal and the constellation dimensions. Our work introduces an iterative decoding strategy with a tolerable complexity order. We consider a MIMO system with finite constellation and model it as a system with sparse signal sources. We propose an ML relaxed detector that minimizes the euclidean distance with the received signal while preserving a constant l1-norm of the decoded signal. We also show that the detection problem is equivalent to a convex optimization problem which is solvable in polynomial time. Two applications are proposed, and simulation results illustrate the efficiency of the proposed detector