Near Optimum Low Complexity Smoothing Loops for Dynamical Phase Estimation—Application to BPSK Modulated Signals

International audience—This correspondence provides and analyzes a low complexity, near optimum, fixed-interval smoothing algorithm that approaches the performance of an optimal smoother for the price of two low complexity sequential estimators, i.e., two phase-locked loops (PLLs). Based on a linear approximation of the problem, a theoretical performance evaluation is given. The theoretical results are compared to some simulation results and to the Bayesian and hybrid Cramér–Rao bounds. They illustrate the good performance of the proposed smoothing PLL (S-PLL) algorithm. Index Terms—Dynamical phase estimation, phase-locked loop (PLL), smoothing algorithm

Bayesian and Hybrid Cramér–Rao Bounds for the Carrier Recovery Under Dynamic Phase Uncertain Channels

International audience—In this paper, we study Bayesian and hybrid Cramér–Rao bounds (BCRB and HCRB) for the code-aided (CA), the data-aided (DA), and the non-data-aided (NDA) dynamical phase estimation of QAM modulated signals. We address the bounds derivation for both the offline scenario, for which the whole observation frame is used, and the online which only takes into account the current and the previous observations. For the CA scenario we show that the computation of the Bayesian information matrix (BIM) and of the hybrid information matrix (HIM) is NP hard. We then resort to the belief-propagation (BP) algorithm or to the Bahl–Cocke–Jelinek–Raviv (BCJR) algorithm to obtain some approximate values. Moreover, in order to avoid the calculus of the inverse of the BIM and of the HIM, we present some closed form expressions for the various CRBs, which greatly reduces the computation complexity. Finally, some simulations allow us to compare the possible improvements enabled by the offline and the CA scenarios. Index Terms—Bayesian Cramér–Rao bound (BCRB), code-aided (CA) bound, data-aided (DA) bound, dynam-ical phase estimation, hybrid Cramér–Rao bound (HCRB), non-data-aided (NDA), offline, online

Performance Study of a Near Maximum Likelihood Code-Aided Timing Recovery Technique

International audienceIn this paper, we propose a new code-aided (CA) timing recovery algorithm for various linear constant modulus constellations based on the Maximum Likelihood (ML) estimator. The first contribution is the derivation of a soft estimator expression of the transmitted symbol instead of its true or hard estimated value which is fed into the timing error detector (TED) equation. The proposed expression includes the Log-Likelihood Ratios (LLRs) obtained from a turbo decoder. Our results show that the proposed CA approach achieves almost as good results as the data-aided (DA) approach over a large interval of SNR values while achieving a higher spectral efficiency. We also derive the corresponding CA Cramer Rao Bounds (CRB) for various modulation orders. Contrarily to former work, we develop here the CRB analytical expression for different M-PSK modulation orders and validate them through comparison to empirical CRB obtained by Monte Carlo iterations. The proposed CA estimator realizes an important gain over the non data-aided approach (NDA) and achieves a smaller gap when compared to its relative CA CRB, especially at moderate SNR values where modern systems are constrained to work

CRB derivation and new Code-Aided timing recovery technique for QAM modulated signals

International audience— * In this paper, we propose a maximum likelihood based Code-Aided (CA) timing recovery algorithm for square-QAM modulated signals. We also theoretically derive the analytical expression of the CA Cramer-Rao Bound for time delay estimation. Our simulations show that the proposed CA approach realizes a performance equivalent to the Data-Aided (DA) approach over a large interval of signal to noise ratio (SNR) values

Optimal scheduling for multiple description video streams in wireless multihop networks

International audience— In this work, we investigate the optimal system scheduling for competing multiple description (MD) video streams in a resource-limited wireless multihop network. By joint optimization of MD, rate control and multipath routing, optimal joint rate control and routing algorithm is proposed to solve this problem with constraints that arise from the MD streams among multiple users via multiple paths. We design this joint algorithm in a distributed manner that is amenable to on-line implementation for wireless networks

A Low Complexity Block Turbo Decoder Architecture

International audienceWe present a low-complexity architecture designed for the decoding of block turbo codes. In particular we simplify the implementation of Pyndiah's algorithm by not memorizing any of the concurrent codewords generated by the Chase search

Analytic and Asymptotic Analysis of Bayesian Cramér-Rao Bound for Dynamical Phase Offset Estimation

International audienceIn this paper, we present a closed-form expression of a Bayesian Cramér-Rao lower bound for the estimation of a dynamical phase offset in a non-data-aided BPSK transmitting context. This kind of bound is derived considering two different scenarios: a first expression is obtained in an off-line context and then, a second expression in an on-line context logically follows. The SNR-asymptotic expressions of this bound drive us to introduce a new asymptotic bound, namely the Asymptotic Bayesian Cramér-Rao Bound. This bound is close to the classical Bayesian bound but is easier to evaluate

Max-log demapper architecture design for DVB-T2 rotated QAM constellations

International audience— Rotated and cyclic-Q delayed (RCQD) quadrature amplitude modulation (QAM) improve DVB-T2 system performance over highly time-frequency selective channels. However, when compared with conventional QAM demapper, the RCQD demapper requires a higher computational complexity. In this paper, a complexity-reduced max-log demapper is derived and implemented over a FPGA platform. The proposed demapper allows to find the maximum likelihood (ML) point with a search spanning only M signal constellation points and guarantees to obtain the same log-likelihood ratio (LLR) metrics as the optimum max-log soft decision demapper while spanning at most 2 M signal constellation points. The optimized hardware implementation introduces only a slight performance loss compared to the floating-point full complexity max-log performance. Index Terms — DVB-T2, Rotated and Cyclic Q Delayed (RCQD) Constellations, Log-Likelihood Ratio (LLR), Max-Log Demapper