A Non-coherent UWB receiver using signal cluster sparsity

Sharma, Sanjeev; Bhatia, Vimal; Gupta, Anubha

doi:10.1109/ncc.2017.8077124

Cited by 8 publications

(4 citation statements)

References 23 publications

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“…where Ñ is the number of samples in s. In (13), signal s is fixed and CDA output signal ŝ changes after each iteration. Hence, MSE in (13) Next, the BER performance of TH-BPSK UWB system in the presence of impulse noise using the proposed receiver and the blanking non-linearity based receiver in [3,16,17] is analyzed in AWGN and multipath IEEE 802.15.4a channel CM1 [12]. Results are shown in Fig.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…This subsection presents a new cluster detection algorithm (CDA) for the proposed receiver design. It is known that the UWB signal cluster is symmetric around the maximum absolute peak value of the transmitted pulse [10,12,13]. This signal cluster symmetry can be used to differentiate between signal cluster and impulse noise samples.…”

Section: A Cluster Detection Algorithmmentioning

confidence: 99%

“…In this paper, we propose a novel signal cluster-detection based receiver design to mitigate impulse noise in a UWB system. The received UWB signal forms clusters due to signal propagation characteristics [4,10,[12][13][14][15] and hence is also called as cluster sparse signal. The proposed cluster detection algorithm easily differentiates between UWB signal cluster and impulse noise.…”

Section: Introductionmentioning

confidence: 99%

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Impulse Noise Mitigation in IR-UWB Communication Using Signal Cluster Sparsity

2018

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In many applications, ultra-wide band (UWB) system experiences impulse noise due to surrounding physical noise sources. Therefore, a conventional receiver (correlator or matched filter) designed for additive Gaussian noise system is not optimum for an impulse noise affected communication channel.In this paper, we propose a new robust receiver design that utilizes the received UWB signal cluster sparsity to mitigate impulse noise. Further, multipath channel diversity enhances the signal-to-noise ratio, as compared to the single path after impulse noise removal in the proposed receiver design. The proposed receiver is analyzed in time hopping binary phase shift keying UWB system and is compared with popular blanking non-linearity based receiver in Bernoulli-Gaussian impulse noise over both single and multipath IEEE 802.15.4a channels. Unlike existing designs, the proposed receiver does not require any training sequence. The proposed receiver is observed to be robust with improved bit error rate performance as compared to a blanking receiver in the presence of impulse noise.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: A Cluster Detection Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impulse Noise Mitigation in IR-UWB Communication Using Signal Cluster Sparsity

2018

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“…Several experiments have been conducted to optimize the UWB transceiver to improve the signal transmission efficiency of UWB. A non-coherent UWB receiver was previously designed by exploiting the cluster-sparsity of the received UWB signal (Sharma et al, 2017 ). The proposed receiver structure enhanced the signal-to-noise ratio at the receiver output compared with the energy detector (ED) by barring inter-clusters noise accumulation.…”

Section: Introductionmentioning

confidence: 99%

UWB indoor positioning optimization algorithm based on genetic annealing and clustering analysis

Guo

Zhang

et al. 2022

Front. Neurorobot.

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Indoor location information is an indispensable parameter for modern intelligent warehouse management and robot navigation. Indoor wireless positioning exhibits large errors due to factors such as indoor non-line-of-sight (NLOS) obstructions. In the present study, the error value under the time of arrival (TOA) algorithm was evaluated, and the trilateral positioning method was optimized to minimize the errors. An optimization algorithm for indoor ultra-wideband (UWB) positioning was designed, which was referred as annealing evolution and clustering fusion optimization algorithm. The algorithm exploited the good local search capability of the simulated annealing algorithm and the good global search capability of the genetic algorithm to optimize cluster analysis. The optimal result from sampled data was quickly determined to achieve effective and accurate positioning. These features reduced the non-direct aiming error in the indoor UWB environment. The final experimental results showed that the optimized algorithm significantly reduced noise interference as well as improved positioning accuracy in an NLOS indoor environment with less than 10 cm positioning error.

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Impulse Radio UWB blind detection using Cross Recurrence Plot

Diaconescu¹

2020

2020 13th International Conference on Communications (COMM)

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A Non-coherent UWB receiver using signal cluster sparsity

Cited by 8 publications

References 23 publications

Impulse Noise Mitigation in IR-UWB Communication Using Signal Cluster Sparsity

Impulse Noise Mitigation in IR-UWB Communication Using Signal Cluster Sparsity

UWB indoor positioning optimization algorithm based on genetic annealing and clustering analysis

Impulse Radio UWB blind detection using Cross Recurrence Plot

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