Channel estimation in UWB channels using compressed sensing

Cohen, Kfir M.; Attias, Chen; Farbman, Barak; Tselniker, Igor; Eldar, Yonina C.

doi:10.1109/icassp.2014.6853942

Cited by 21 publications

(16 citation statements)

References 19 publications

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“…We sidestep this requirement by adopting cognitive transmission wherein the analog signal of each channel lives only in certain pre-determined subbands and consequently, a BPF stage is not required. More importantly, for each channel, a single low-rate ADC can subsample this narrow-band signal as long as the subbands are coset bands so that they don't aliase after sampling [21]. This implementation needs only eight low-rate ADCs, one per channel.…”

Section: A Design Philosophymentioning

confidence: 99%

Cognitive sub-Nyquist hardware prototype of a collocated MIMO radar

Mishra

Shoshan

Namer

et al. 2016

2016 4th International Workshop on Compressed Sensing Theory and Its Applications to Radar, Sonar and Remote Sensing (CoSeRa)

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Abstract-We present the design and hardware implementation of a radar prototype that demonstrates the principle of a sub-Nyquist collocated multiple-input multiple-output (MIMO) radar. The setup allows sampling in both spatial and spectral domains at rates much lower than dictated by the Nyquist sampling theorem. Our prototype realizes an X-band MIMO radar that can be configured to have a maximum of 8 transmit and 10 receive antenna elements. We use frequency division multiplexing (FDM) to achieve the orthogonality of MIMO waveforms and apply the Xampling framework for signal recovery. The prototype also implements a cognitive transmission scheme where each transmit waveform is restricted to those pre-determined subbands of the full signal bandwidth that the receiver samples and processes. Real-time experiments show reasonable recovery performance while operating as a 4 × 5 thinned random array wherein the combined spatial and spectral sampling factor reduction is 87.5% of that of a filled 8 × 10 array.

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Section: A Design Philosophymentioning

confidence: 99%

Cognitive sub-Nyquist hardware prototype of a collocated MIMO radar

Mishra

Shoshan

Namer

et al. 2016

2016 4th International Workshop on Compressed Sensing Theory and Its Applications to Radar, Sonar and Remote Sensing (CoSeRa)

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“…Some recent researches have shown the great potential of applying CS to the design of IR-UWB communication systems as well as IR-UWB radar systems. For example, CS is used to achieve high performance IR-UWB channel estimation by exploring the channel sparsity [22,23]; novel IR-UWB symbol detection strategies are designed under the CS framework [24][25][26][27] by exploring the transmitted signal sparsity; based on low-rate compressive measurements, new echo detection methods for IR-UWB radar imaging are proposed [28,29]. Taking into account the sparse character of narrowband interference in the frequency domain, CS-based narrowband interference mitigation methods are also proposed for IR-UWB communications [30].…”

Section: Background and Related Workmentioning

confidence: 99%

High precision ranging with IR-UWB: a compressed sensing approach

Zhang

Zhou

et al. 2016

Wirel. Commun. Mob. Comput.

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Ranging has been regarded as one of the fundamental enabling technologies for a multitude of applications that require high accurate position information, such as automated navigation, vehicle platooning, asset management, etc. Among various ranging techniques, impulse-radio ultra-wideband is one of the most competitive technologies for high-precision ranging, because of its capability of achieving centimeter-level ranging accuracy, even for dense urban, indoor or cave like environments. However, two main challenges arise when fully exploiting the ranging capability of impulse-radio ultrawideband: (i) the extremely high sampling rate to acquire the received multipath signal, and (ii) the optimal thresholding strategy to differentiate the first path. To efficiently tackle those challenges, in this work, we propose a ranging approach under the compressed sensing framework. Specifically, the received ranging signal is acquired by low-rate compressed sampling through parallel random projections. Then, an algorithm named matching-pursuit search-back is proposed to detect the first arrival path, which integrates a backward iterative search and thresholding process starting from the peak path. The detection threshold is dynamically adjusted in each iteration to asymptotically minimize the averaged detection errors over false alarm and missed detection. Extensive simulations and experiments with field data are provided to demonstrate that the proposed approach can achieve high-precision ranging with far fewer samples compared with the traditional Nyquist-sampling based ones.

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“…Many algorithms for TD estimation from frequency domain samples have been proposed in the past. These algorithms are usually based on (i) subspace estimation [3,4,5,6], (ii) finite rate of innovation [2,7,8], or (iii) compressed sampling [9,10,11,12,13,14] methods. Few of the previous works [8,10,11,14] discuss issues related to frequency domain sampling.…”

Section: Introductionmentioning

confidence: 99%

Time Delay Estimation from Multiband Radio Channel Samples in Nonuniform Noise

Kazaz

Janssen

Veen

2019

2019 53rd Asilomar Conference on Signals, Systems, and Computers

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The multipath radio channel is considered to have a non-bandlimited channel impulse response. Therefore, it is challenging to achieve high resolution time-delay (TD) estimation of multipath components (MPCs) from bandlimited observations of communication signals. It this paper, we consider the problem of multiband channel sampling and TD estimation of MPCs. We assume that the nonideal multibranch receiver is used for multiband sampling, where the noise is nonuniform across the receiver branches. The resulting data model of Hankel matrices formed from acquired samples has multiple shiftinvariance structures, and we propose an algorithm for TD estimation using weighted subspace fitting. The subspace fitting is formulated as a separable nonlinear least squares (NLS) problem, and it is solved using a variable projection method. The proposed algorithm supports high resolution TD estimation from an arbitrary number of bands, and it allows for nonuniform noise across the bands. Numerical simulations show that the algorithm almost attains the Cramér Rao Lower Bound, and it outperforms previously proposed methods such as multiresolution TOA, MI-MUSIC, and ESPRIT.

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Channel estimation in UWB channels using compressed sensing

Cited by 21 publications

References 19 publications

Cognitive sub-Nyquist hardware prototype of a collocated MIMO radar

Cognitive sub-Nyquist hardware prototype of a collocated MIMO radar

High precision ranging with IR-UWB: a compressed sensing approach

Time Delay Estimation from Multiband Radio Channel Samples in Nonuniform Noise

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