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A Unified Multi-Functional Dynamic Spectrum Access Framework: Tutorial, Theory and Multi-GHz Wideband Testbed
- SENSORS
, 2009
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Decentralized Turbo Bayesian Compressed Sensing with Application to
- UWB Systems,” EURASIP J. Adv. Sig. Proc
"... which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In many situations, there exist plenty of spatial and temporal redundancies in original signals. Based on this observation, a novel Turbo Bayesian Compressed Sensing (TBCS) alg ..."
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which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In many situations, there exist plenty of spatial and temporal redundancies in original signals. Based on this observation, a novel Turbo Bayesian Compressed Sensing (TBCS) algorithm is proposed to provide an efficient approach to transfer and incorporate this redundant information for joint sparse signal reconstruction. As a case study, the TBCS algorithm is applied in Ultra-Wideband (UWB) systems. A space-time TBCS structure is developed for exploiting and incorporating the spatial and temporal a priori information for space-time signal reconstruction. Simulation results demonstrate that the proposed TBCS algorithm
Performance Analysis and Optimization of Tc-DTR IR-UWB Receivers over Multipath Fading Channels with Tone Interference,” Vehicular Technology
- IEEE Transactions on
"... Abstract — In this paper, we analyze the performance of a particular class of Transmitted–Reference (TR) receivers for Impulse Radio (IR–) Ultra Wide Band (UWB) communication systems, which is called Chip–Time Differential Transmitted– Reference (Tc–DTR). The analysis aims at investigating the robus ..."
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Abstract — In this paper, we analyze the performance of a particular class of Transmitted–Reference (TR) receivers for Impulse Radio (IR–) Ultra Wide Band (UWB) communication systems, which is called Chip–Time Differential Transmitted– Reference (Tc–DTR). The analysis aims at investigating the robustness of this receiver to single – and multi–tone Narrow–Band Interference (NBI), and at comparing its performance with other non–coherent receivers proposed in the literature. It is shown that the Tc–DTR scheme provides more degrees of freedom for performance optimization, and it is inherently more robust to NBI than other non–coherent receivers. More specifically, it is analytically proved that the performance improvement is due to the chip–time level differential encoding/decoding of the Direct Sequence (DS) code, and to an adequate design of DS code and average pulse repetition time. The analysis encompasses performance metrics that are useful for both data detection (i.e., Average Bit Error Probability, ABEP) and timing acquisition (i.e., False Alarm Probability, Pfa, and Detection Probability, Pd). Moving from the proposed semi–analytical framework, the optimal code design and system parameters are derived, and it is highlighted that the same optimization criterion can be applied to all performance metrics considered in this paper. Also, analytical frameworks and theoretical findings are substantiated via Monte Carlo simulations. Index Terms — Ultra wide band (UWB), impulse radio (IR), transmitted–reference (TR), tone interference, multipath fading channels, code design, performance analysis. I.
Wireless Tomography, Part III: Compressed Sensing for Ultra-wideband Signals
"... This is Part III of the wireless tomography three-paper series. Wireless tomography is related to wireless communications in that it requires the channel recovery between different waveforms at transmit and receive, as well as multiple-input-multiple-output (MIMO) communication system. According to ..."
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This is Part III of the wireless tomography three-paper series. Wireless tomography is related to wireless communications in that it requires the channel recovery between different waveforms at transmit and receive, as well as multiple-input-multiple-output (MIMO) communication system. According to the pulse propagation mechanisms of reflection and diffraction, ultra-wideband (UWB) waveforms suffer pulse distortion. Distorted pulses will overlap and therefore increases the sampling rate for accurate UWB channel recovery. Thanks to the recent progresses in sampling theory and radio propagation theory, we are able to propose a compressed sensing (CS) based UWB channel recovery method considering pulse distortion. The concept has been demonstrated through simulations. The sampling rate is as low as 2 Gsps, compared with the Nyquist rate of 50 Gsps. A CS based 2×2 MIMO communication system is also proposed and simulated. The communication problem is modeled as CS problem, and further reduce sampling rate required at the receiver.
Compressive Sampling Based Energy Detection of Ultra-Wideband Pulse Position Modulation
"... Abstract—Compressive sampling (CS) based energy detectors are developed for ultra-wideband (UWB) pulse position modula-tion (PPM), in multipath fading environments so as to reduce the sampling complexity at the receiver side. Due to sub-Nyquist rate sampling, the CS process outputs a compressed vers ..."
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Abstract—Compressive sampling (CS) based energy detectors are developed for ultra-wideband (UWB) pulse position modula-tion (PPM), in multipath fading environments so as to reduce the sampling complexity at the receiver side. Due to sub-Nyquist rate sampling, the CS process outputs a compressed version of the re-ceived signal such that the original signal can be recovered from this low dimensional representation. Using the principles of gener-alizedmaximum likelihood (GML), we propose two types of energy detectors for such signals. The first type of detectors involves the reconstruction of the received signal followed by a detection stage. Statistical properties of the reconstruction error have been used for the realization of such kind of detectors. The second type of detectors does not rely on reconstruction and carries out the detec-tion operation directly on the compressed signal, thereby offering a further reduction in the implementation complexity. The perfor-mance of the proposed detectors is independent of the spreading factor. We analyze the bit error performance of the proposed en-ergy detectors for two scenarios of the propagation channel: when the channel is deterministic, and when it is Gaussian distributed. We provide exact bit error probability (BEP) expressions of the CS based energy detectors for each scenario of the channel. The BEP expressions obtained for the detectors working on the com-pressed signal directly can naturally be extended to BEP expres-sions for the related energy detectors working on the Nyquist-rate sampled signal. Simulation results validate the accuracy of these BEP expressions. Index Terms—Compressive sampling, energy detection, pulse position modulation, ultra-wideband impulse radio. I.
1 Modified Orthogonal Matching Pursuit Algorithm for Cognitive Radio Wideband Spectrum Sensing
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Compressed Sensing for OFDM UWB Systems
"... Abstract—This paper considers compressed sensing (CS) techniques for signal reconstruction and channel estimation in OFDM-based high-rate ultra wideband (UWB) communication systems. We employ a parallel CS structure that exploits frequency domain sparsity. We also consider multipath UWB channels in ..."
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Abstract—This paper considers compressed sensing (CS) techniques for signal reconstruction and channel estimation in OFDM-based high-rate ultra wideband (UWB) communication systems. We employ a parallel CS structure that exploits frequency domain sparsity. We also consider multipath UWB channels in both the line-of-sight and non line-of-sight environments. UWB signal detection and channel estimation from sub-Nyquist analog projections is carried out using an optimized orthogonal matching pursuit algorithm and the smoothed ℓ0 algorithm. Simulation results demonstrate significant gains in the form of reliable signal recovery and channel estimation as well as dramatically sub-Nyquist sampling rates for the analog-to-digital converters while maintaining high data rates. Index Terms—Channel estimation, compressed sensing, multipath channels, OFDM, signal reconstruction, UWB. I.
Compressed Sensing and its Applications in UWB Communication Systems
"... Abstract—Ultra-wideband (UWB) communication systems can be used as overlay over existing systems due to their large absolute bandwidth and low power spectral density. But real-ization of UWB systems has been obstructed due to present state of art of A/D converters that are not able to meet the high ..."
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Abstract—Ultra-wideband (UWB) communication systems can be used as overlay over existing systems due to their large absolute bandwidth and low power spectral density. But real-ization of UWB systems has been obstructed due to present state of art of A/D converters that are not able to meet the high sampling rate requirement of UWB systems. Compressed sensing appears to be a natural solution to develop systems with sub-Nyquist sampling. In this paper, a short survey of compressed sensing and its application to UWB communication systems is presented. The original formulation of the compressed sensing problem is formulated, and UWB paradigm is discussed. A compressed sensing based signal detector is studied along with a its application to maximum likelihood (ML) channel estimation under a common systemic framework. A channel pre-coding based compressive measurement scheme is also presented which significantly reduces the receiver side processing. Results pertaining to system performance are also presented. This paper explores the application of the emerging field of compressive sensing in UWB systems. Index Terms—Compressed sensing, UWB communication sys-tems, channel estimation, signal detection. I.
Approved for the Faculty:
, 2009
"... The demanding characteristics of the UWB technology include ex-tremely high sampling rates in the receiver. These sampling rates require sophisticated devices, sometimes out of the scope of the state-of-art tech-nology. Among the different methods to make the reception possible, Compressed Sensing s ..."
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The demanding characteristics of the UWB technology include ex-tremely high sampling rates in the receiver. These sampling rates require sophisticated devices, sometimes out of the scope of the state-of-art tech-nology. Among the different methods to make the reception possible, Compressed Sensing seems to be the one that presents better perfor-mance. It consists basically of compressing the information while this is sampled, avoiding processing a huge chunk of redundant data and low-ering the sampling rate. In order to reconstruct the data after the com-pression, different methods have come up presenting different favorable features. However this methods also present a trade-off between sam-pling rate and processing time. Using real measurements of the channel, the performance in different environments has been analyzed for different frequencies. Thanks to the theoretical account and practical results this study will help to understand better the Compressed Sensing techniques applied to a real communication, and specifically, to Ultra Wideband.
Research Article Decentralized Turbo Bayesian Compressed Sensing with Application to UWB Systems
"... which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In many situations, there exist plenty of spatial and temporal redundancies in original signals. Based on this observation, a novel Turbo Bayesian Compressed Sensing (TBCS) alg ..."
Abstract
- Add to MetaCart
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which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In many situations, there exist plenty of spatial and temporal redundancies in original signals. Based on this observation, a novel Turbo Bayesian Compressed Sensing (TBCS) algorithm is proposed to provide an efficient approach to transfer and incorporate this redundant information for joint sparse signal reconstruction. As a case study, the TBCS algorithm is applied in Ultra-Wideband (UWB) systems. A space-time TBCS structure is developed for exploiting and incorporating the spatial and temporal a priori information for space-time signal reconstruction. Simulation results demonstrate that the proposed TBCS algorithm achieves much better performance with only a few measurements in the presence of noise, compared with the traditional Bayesian Compressed Sensing (BCS) and multitask BCS algorithms. 1.