Recognition of a code in a noisy environment

Chabot, Christophe

doi:10.1109/isit.2007.4557548

Cited by 39 publications

(39 citation statements)

References 4 publications

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“…As a benchmark for comparison, we also implemented the test proposed in [13]. However, since the algorithm therein can only be used in binary symmetric channels (BSC), we consider an equivalent BSC channel with cross-over probability equal to the error probability of the AWGN channel in our model with BPSK modulation.…”

Section: B Application Of the Code Detection Scheme To Convolutionalmentioning

confidence: 99%

“…Figures 4(a)-4(c) illustrate the ROC curves of the different schemes for the case where the SNR is 0 dB and for two different values of N b for the three convolutional codes, respectively. More precisely, we have provided ROC curves for (i) the statistical test given by (12), (ii) the suboptimal test given by (13), (iii) the suboptimal test where in addition to (13), we also used the approximation given by (11) in computing γ i , (iv) our analysis provided by (20), and (v) the test using the algorithm in [13]. 12 As the results show, the proposed statistical test (i) has better performance compared to the other tests, specially compared to the test in [13].…”

Section: B Application Of the Code Detection Scheme To Convolutionalmentioning

confidence: 99%

“…However, these schemes can only be applied for recognition of specific codes. In [13], an algorithm for blind recognition of a linear code in a binary symmetric channel (BSC) was proposed. In order to determine if a certain code with a given parity check matrix was used to encode the data, the author therein proposed to first take hard decisions on the received data to get a rough estimate of the transmitted codeword, and then to find the inner products between the estimated codeword and the rows of the parity check matrix and use this quantity to determine whether the data was encoded with the given channel code or not.…”

Section: Introductionmentioning

confidence: 99%

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Fast Blind Recognition of Channel Codes

Moosavi

Larsson

2014

IEEE Trans. Commun.

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Abstract-We present a fast algorithm that, for a given input sequence and a linear channel code, computes the syndrome posterior probability (SPP) of the code, i.e., the probability that all parity check relations of the code are satisfied. According to this algorithm, the SPP can be computed blindly, i.e., given the soft information on a received sequence we can compute the SPP for the code without first decoding the bits. We show that the proposed scheme is efficient by investigating its computational complexity.We then consider two scenarios where our proposed SPP algorithm can be used. The first scenario is when we are interested in finding out whether a certain code was used to encode a data stream. We formulate a statistical hypothesis test and we investigate its performance. We also compare the performance of our scheme with that of an existing scheme. The second scenario deals with how we can use the algorithm for reducing the computational complexity of a blind decoding process. We propose a heuristic sequential statistical hypotheses test to use the fact that in real applications, the data arrives sequentially, and we investigate its performance using system simulations.

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Section: B Application Of the Code Detection Scheme To Convolutionalmentioning

confidence: 99%

Section: B Application Of the Code Detection Scheme To Convolutionalmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fast Blind Recognition of Channel Codes

Moosavi

Larsson

2014

IEEE Trans. Commun.

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“…When it is known that the channel code has been chosen from a set of predefined candidate set, the receiver can use this a priori information for achieving a better blind channel code identification. This problem was addressed in [41][42][43].…”

Section: Research Related To Signaling Overheadmentioning

confidence: 99%

Improving the Efficiency of Control Signaling in Wireless Multiple Access Systems

Moosavi¹

2013

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To my lovely wife, my beloved parents, and my dear sisters; without them I would not be here."Even if you are on the right track, you'll get run over if you just sit there." Will Rogers AbstractPrior to the transmission of payload data in any multiple access system, there is generally a need to send control information such as scheduling assignments, transmission parameters and HARQ acknowledgments. This process is called control signaling and has a significant impact on the overall system performance. This dissertation considers different aspects of control signaling and proposes some novel schemes for improving it. The dissertation is split into two parts where in the first part the focus is on the transmission of scheduling assignments, and in the second part the focus is on improving the "blind decoding" process that is used to achieve adaptive coding and modulation in transmission of control information.More specifically, in the first part of the dissertation we first compare the two conventional schemes for control signaling using extensive system simulations. In doing so, we use practical assumptions on the scheduling algorithm as well as on the compression and transmission of the scheduling information. We then provide two schemes for reducing the amount of control signaling that concerns the transmission of scheduling assignments. The first scheme, which is reminiscent of source coding with side information, uses the knowledge that each user has about its own channel condition to compress the scheduling information more effectively. The second scheme uses the fact that in wireless multiple access systems, a user with a given channel condition can in principle decode the data intended to the users that have weaker channels. Therefore, the idea is to send the scheduling information of different terminals in a differential manner starting from the user with the weakest channel and letting all the terminals overhear the transmission of one another. Finally, in the last section of this part we use some of the recent results in information theory to form a general framework for the comparison of different control signaling schemes. We formulate an optimization problem that for a given desired error probability finds the minimum required number of channel uses for a given signaling scheme.In the second part of the thesis, we propose three schemes for reducing the complexity of the blind decoding process. The first one is a novel scheme for fast blind identification of channel codes. More precisely, we propose an efficient algorithm that for a given sequence of received symbols and a given linear channel code, finds the posterior probability that all the parity check relations of the code are satisfied. We then use this quantity to perform a sequential statistical hypotheses test that vii reduces the computational complexity of blind decoding. The idea in the second scheme is to broadcast a control message prior to the transmission of control information to instruct only a subset of the terminals (ideally only ...

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“…But he does not know anything about the characteristics of the different elements except the noisy channel, and so his first goal is to determine which elements have been used in the communication system. This problem arises for instance in a military context ; reverse engineering of the error correction component has been studied in [8], [1], [2] whereas reverse engineering of the scrambler has been considered in [3].…”

Section: Introductionmentioning

confidence: 99%