Results 1  10
of
61
Joint iterative detection and decoding in the presence of phase noise and frequency offset
 in Proc. IEEE Intern. Conf. Commun
, 2005
"... Abstract—We present a new algorithm for joint detection and decoding of iteratively decodable codes transmitted over channels affected by a timevarying phase noise (PN) and a constant frequency offset. The proposed algorithm is obtained as an application of the sumproduct algorithm to the factor g ..."
Abstract

Cited by 19 (6 self)
 Add to MetaCart
Abstract—We present a new algorithm for joint detection and decoding of iteratively decodable codes transmitted over channels affected by a timevarying phase noise (PN) and a constant frequency offset. The proposed algorithm is obtained as an application of the sumproduct algorithm to the factor graph representing the joint a posteriori distribution of the information symbols and the channel parameters given the channel output. The resulting algorithm employs the softoutput information on the coded symbols provided by the decoder and performs forward– backward recursions, taking into account the joint probability distribution of phase and frequency offset. We present simulation results for highorder coded modulation schemes based on lowdensity paritycheck codes and serially concatenated convolutional codes, showing that, despite its low complexity, the algorithm is able to cope with a strong PN and a significant uncompensated frequency offset, thus avoiding the use of complicated dataaided frequencyestimation schemes operating on a known preamble. The robustness of the algorithm in the presence of a timevarying frequency offset is also discussed. Index Terms—Detection and decoding in the presence of phase noise and frequency offset, factor graphs (FGs), iterative detection and decoding, lowdensity paritycheck (LDPC) codes, serially concatenated convolutional codes (SCCCs), sumproduct algorithm (SPA), turbo codes (TCs). I.
On LDPC codes over channels with memory
 IEEE Trans. Wireless Commun
, 2006
"... Abstract — The problem of detection and decoding of lowdensity paritycheck (LDPC) codes transmitted over channels with memory is addressed. A new general method to build a factor graph which takes into account both the code constraints and the channel behavior is proposed and the a posteriori proba ..."
Abstract

Cited by 18 (12 self)
 Add to MetaCart
(Show Context)
Abstract — The problem of detection and decoding of lowdensity paritycheck (LDPC) codes transmitted over channels with memory is addressed. A new general method to build a factor graph which takes into account both the code constraints and the channel behavior is proposed and the a posteriori probabilities of the information symbols, necessary to implement maximum a posteriori (MAP) symbol detection, are derived by using the sumproduct algorithm. With respect to the case of a LDPC code transmitted on a memoryless channel, the derived factor graphs have additional factor nodes taking into account the channel behavior and not the code constraints. It is shown that the function associated to the generic factor node modeling the channel is related to the basic branch metric used in the Viterbi algorithm when MAP sequence detection is applied or in the BCJR algorithm implementing MAP symbol detection. This fact suggests that all the previously proposed solutions for those algorithms can be systematically extended to LDPC codes and graphbased detection. When the sumproduct algorithm works on the derived factor graphs, the most demanding computation is in general that performed at factor nodes modeling the channel. In fact, the complexity of the computation at these factor nodes is in general exponential in a suitably defined channel memory parameter. In these cases, a technique for complexity reduction is illustrated. In some particular cases of practical relevance, the above mentioned complexity becomes linear in the channel memory. This does not happen in the same cases when detection is performed by using the Viterbi algorithm or the BCJR algorithm, suggesting that the use of factor graphs and the sumproduct algorithm might be computationally more appealing. As an example of application of the described framework, the cases of noncoherent and flat fading channels are considered. Index Terms — Factor graphs, sumproduct algorithm, channels with memory, phasenoise, flat fading, lowdensity paritycheck codes, iterative detection/decoding. I.
Timefrequency packing for linear modulations: spectral efficiency and practical detection schemes
 IEEE Trans. Commun
, 2009
"... Abstract — We investigate the spectral efficiency, achievable by a lowcomplexity symbolbysymbol receiver, when linear modulations based on the superposition of uniformly time and frequencyshifted replicas of a base pulse are employed. Although orthogonal signaling with Gaussian inputs achieves ..."
Abstract

Cited by 15 (13 self)
 Add to MetaCart
(Show Context)
Abstract — We investigate the spectral efficiency, achievable by a lowcomplexity symbolbysymbol receiver, when linear modulations based on the superposition of uniformly time and frequencyshifted replicas of a base pulse are employed. Although orthogonal signaling with Gaussian inputs achieves capacity on the additive white Gaussian noise channel, we show that, when finiteorder constellations are employed, by giving up the orthogonality condition (thus accepting interference among adjacent signals) we can considerably improve the performance, even when a symbolbysymbol receiver is used. We also optimize the spacing between adjacent signals to maximize the achievable spectral efficiency. Moreover, we propose a more involved transmission scheme, composed by the superposition of two independent signals and a receiver based on successive interference cancellation, showing that it allows a further increase of the spectral efficiency. Finally, we show that a more involved equalization algorithm, based on soft interference cancellation, allows to achieve an excellent biterrorrate performance, even when errorcorrecting codes designed for the Gaussiannoiselimited channel are employed, and thus does not require a complete redesign of the coding scheme. I.
Joint Estimation of Channel and Oscillator Phase Noise in MIMO Systems
"... Abstract—Oscillator phase noise limits the performance of high speed communication systems since it results in time varying channels and rotation of the signal constellation from symbol to symbol. In this paper, joint estimation of channel gains andWiener phase noise in multiinput multioutput (MIM ..."
Abstract

Cited by 13 (7 self)
 Add to MetaCart
Abstract—Oscillator phase noise limits the performance of high speed communication systems since it results in time varying channels and rotation of the signal constellation from symbol to symbol. In this paper, joint estimation of channel gains andWiener phase noise in multiinput multioutput (MIMO) systems is analyzed. The signal model for the estimation problem is outlined in detail and new expressions for the CramérRao lower bounds (CRLBs) for the multiparameter estimation problem are derived. A dataaided leastsquares (LS) estimator for jointly obtaining the channel gains and phase noise parameters is derived. Next, a decisiondirected weighted leastsquares (WLS) estimator is proposed, where pilots and estimated data symbols are employed to track the timevarying phase noise parameters over a frame. In order to reduce the overhead and delay associated with the estimation process, a new decisiondirected extended Kalman filter (EKF) is proposed for tracking the MIMO phase noise throughout a frame. Numerical results show that the proposed LS, WLS, and EKF estimators ’ performances are close to the CRLB. Finally, simulation results demonstrate that by employing the proposed channel and timevarying phase noise estimators the biterror rate performance of a MIMO system can be significantly improved. Index Terms—Channel estimation, CramérRao lower bound (CRLB), extended Kalman filter (EKF), multiinput multioutput (MIMO), weighted least squares (WLS), Wiener phase noise.
Iterative informationreduced carrier synchronization using decision feedback for low SNR applications
 TDA Progress Report
, 1997
"... Abstract — This paper addresses the carrierphase estimation problem under low SNR conditions as are typical of turboand LDPCcoded applications. In [1], [2] closedloop carrier synchronization schemes for errorcorrection coded BPSK and QPSK modulation were proposed that were based on feeding back ..."
Abstract

Cited by 8 (4 self)
 Add to MetaCart
(Show Context)
Abstract — This paper addresses the carrierphase estimation problem under low SNR conditions as are typical of turboand LDPCcoded applications. In [1], [2] closedloop carrier synchronization schemes for errorcorrection coded BPSK and QPSK modulation were proposed that were based on feeding back hard data decisions at the input of the loop, the purpose being to remove the modulation prior to attempting to track the carrier phase as opposed to the more conventional decisionfeedback schemes that incorporate such feedback inside the loop. In this paper, we consider an alternative approach wherein the soft information from the iterative decoder of turbo or LDPC codes is instead used as the feedback. I.
Simplified softoutput detection of CPM signals over coherent and phase noise channels
 IEEE Trans. Wireless Commun
, 2007
"... Abstract — We consider continuous phase modulations (CPMs) in iteratively decoded serially concatenated schemes. Although the overall receiver complexity mainly depends on that of the CPM detector, almost all papers in the literature consider the optimal maximum a posteriori (MAP) symbol detection a ..."
Abstract

Cited by 7 (5 self)
 Add to MetaCart
(Show Context)
Abstract — We consider continuous phase modulations (CPMs) in iteratively decoded serially concatenated schemes. Although the overall receiver complexity mainly depends on that of the CPM detector, almost all papers in the literature consider the optimal maximum a posteriori (MAP) symbol detection algorithm and only a few attempts have been made to design lowcomplexity suboptimal schemes. This problem is faced in this paper by first considering the case of an ideal coherent detection, then extending it to the more interesting case of a transmission over a typical satellite channel affected by phase noise. In both cases, we adopt a simplified representation of an Mary CPM signal based on the principal pulses of its Laurent decomposition. Since it is not possible to derive the exact detection rule by means of a probabilistic reasoning, the framework of factor graphs (FGs) and the sumproduct algorithm (SPA) is used. In the case of channels affected by phase noise, continuous random variables representing the phase samples are explicitly introduced in the FG. By pursuing the principal approach to manage continuous random variables in a FG, i.e., the canonical distribution approach, two algorithms are derived which do not require the presence of known (pilot) symbols, thanks to the intrinsic differential encoder embedded in the CPM modulator. Index Terms — Factor graphs, sumproduct algorithm, continuous phase modulation, iterative detection and decoding, detection and decoding in the presence of phase noise. I.
Variational bayesian framework for receiver design in the presence of phase noise
 in MIMO systems,” Proc. IEEE WCNC
, 2012
"... This document has been downloaded from Chalmers Publication Library (CPL). It is the author´s ..."
Abstract

Cited by 6 (5 self)
 Add to MetaCart
(Show Context)
This document has been downloaded from Chalmers Publication Library (CPL). It is the author´s
On the CramerRao bound for carrier frequency estimation in the presence of phase noise
, 2007
"... We consider the carrier frequency offset estimation in a digital burstmode satellite transmission affected by phase noise. The corresponding CramerRao lower bound is analyzed for linear modulations under a Wiener phase noise model and in the hypothesis of knowledge of the transmitted data. Even i ..."
Abstract

Cited by 5 (4 self)
 Add to MetaCart
We consider the carrier frequency offset estimation in a digital burstmode satellite transmission affected by phase noise. The corresponding CramerRao lower bound is analyzed for linear modulations under a Wiener phase noise model and in the hypothesis of knowledge of the transmitted data. Even if we resort to a Monte Carlo average, from a computational point of view the evaluation of the CramerRao bound is very hard. We introduce a simple but very accurate approximation that allows to carry out this task in a very easy way. As it will be shown, the presence of the phase noise produces a remarkable performance degradation of the frequency estimation accuracy. In addition, we provide asymptotic expressions of the CramerRao bound, from which the effect of the phase noise and the dependence on the system parameters of the frequency offset estimation accuracy clearly result. Finally, as a byproduct of our derivations and approximations, we derive a couple of estimators specifically tailored for the phase noise channel that will be compared with the classical Rife and Boorstyn algorithm, gaining in this way some important hints on the estimators to be used in this scenario.
Optimal and Approximate Methods for Detection of Uncoded Data with Carrier Phase Noise
"... Abstract — Previous results in the literature have shown that derivation of the optimum maximumlikelihood (ML) receiver for symbolbysymbol (SBS) detection of an uncoded data sequence in the presence of random phase noise is an intractable problem, since it involves the computation of the conditio ..."
Abstract

Cited by 5 (5 self)
 Add to MetaCart
(Show Context)
Abstract — Previous results in the literature have shown that derivation of the optimum maximumlikelihood (ML) receiver for symbolbysymbol (SBS) detection of an uncoded data sequence in the presence of random phase noise is an intractable problem, since it involves the computation of the conditional probability distribution function (PDF) of the phase noise process. In this paper, we seek to minimize symbol error probability (SEP), which is achieved by SBS detection of the sequence based on all received signals. We show that the ML detector for this problem can be formulated as a weighted sum of central moments of the conditional PDF of phase noise. Given that the central moments of the conditional PDF of phase noise can be estimated, this new optimal structure is tractable with respect to the previously known optimal ML receiver. Furthermore, based on the new receiver structure, we propose a simple approximate method for SBS detection and investigate its scope and applicability. Simulation results demonstrate that SEP performance close to optimality can be obtained through the proposed method for scenarios of low phase noise variance and low signaltonoise ratio (SNR). I.