Browsing by Author "Wu, Jwo-Yuh"

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A Cooperative Multi-Group Priority MAC Protocol for Multi-Packet Reception Channels
(2009-11-01)
Yang, Wen-Fang
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Wu, Jwo-Yuh
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Wang, Li-Chun
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Lee, Ta-Sung
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電子工程學系及電子研究所
Medium access control (MAC) protocol design for cooperative networks over multi-packet reception (MPR) channels is a challenging topic, but has not been addressed in the literature yet. In this paper, we propose a cooperative multi-group priority (CMGP) based MAC protocol to exploit the cooperation diversity for throughput enhancement over MPR channels. The proposed approach can bypass the computationally-intensive active user identification process. Moreover, our method can efficiently utilize the idle periods for packet relaying, and can thus effectively limit the throughput loss resulting from the relay phase. By means of a Markov chain model, the worst-case throughput analysis is conducted. The results allow us to investigate the throughput performance of the proposed CMGP protocol directly in terms of the MPR channel coefficients. Simulation results confirm the system-wide throughput advantage achieved by the proposed scheme, and also validate the analytic results.
A Low-Complexity Direction-of-Arrival Estimation Algorithm for Full-Dimension Massive MIMO Systems
(2014)
Yang, Kai-Yu
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Wu, Jwo-Yuh
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Li, Wen-Hsuan
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電機工程學系
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Department of Electrical and Computer Engineering
Full dimension (FD) MIMO, whereby a 2-dimensional (2D) antenna array is placed at the base station, has been known as a promising solution to economize spatial size of practical massive MIMO systems. To exploit such spatial resource for system performance enhancement, e.g., via three-dimensional beamforming, accurate estimation of the direction-of-arrival (DoA) of the signal sources is necessary. Existing DoA estimation methods using 2D arrays typically resorted to joint search over the 2D angular domain; however, the required algorithmic complexity would be prohibitively large, especially in the massive MIMO scenario. This paper proposes a two-stage low-complexity DoA estimation scheme, in which two MUSIC algorithms are performed for estimating, respectively, the elevation and azimuth angles of the impinging sources. Detailed flop count analyses are provided for justifying the low-complexity advantage. Various numerical simulations are also used to illustrate the performance of the proposed scheme.
A Multi-Group Priority Based Cooperative MAC Protocol for Multi-Packet Reception Channels
(2009)
Yang, Wen-Fang
;
Wu, Jwo-Yuh
;
Wang, Li-Chun
;
Lee, Ta-Sung
;
電信工程研究所
Medium access control (MAC) protocol design for cooperative networks over multi-packet reception (MPR) channels is a challenging topic, but has not been addressed in the literature yet. In this paper, we propose a MAC protocol to exploit the cooperation diversity for throughput enhancement over MPR channels. The proposed approach can efficiently utilize the idle periods for packet relaying, and can thus effectively limit the throughput loss resulting from the relay phase. By means of a Markov chain model, the worst-case throughput analysis is conducted. Specifically, we derive (i) a closed-form upper bound for the throughput penalty of the direct link that is caused by the interference of concurrent packet relay transmission; (ii) a closed-form lower bound for the throughput gain that a user with packet transmission failure can benefit thanks to cooperative packet relaying. The results allow us to investigate the throughput performance of the proposed protocol directly in terms of the MPR channel coefficients. Simulation results confirm the system-wide throughput advantage achieved by the proposed scheme, and also validate the analytic results.
A multigroup priority queueing MAC protocol for wireless networks with multipacket reception
(2008)
Yang, Wen-Fang
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Wu, Jwo-Yuh
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Wang, Li-Chun
;
Lee, Ta-Sung
;
電信工程研究所
Relying on a simple flag-assisted mechanism, a multigroup priority queueing (MGPQ) medium access control (MAC) protocol is proposed for the wireless networks with multipacket reception ( MPR). The proposed MGPQ scheme is capable of overcoming two major performance bottlenecks inherent in the existing MPR MAC protocols. First, the proposed solution can automatically produce the list of active users by observing the network traffic conditions, remove the need of active user estimation algorithm, and thus can largely reduce the algorithm complexity. Second, the packet blocking constraint imposed on the active users for keeping compliant with prediction is relaxed. As a result, the proposed MGPQ is not only applicable to both homogeneous and heterogeneous cases, but also outperforms the existing MPRMAC protocols. Simulation results show that the network throughput can be improved by 40% maximum and 14% average as compared with the well- known dynamic queue (DQ) MAC protocol.
A Neyman-Pearson Type Sensor Censoring Scheme for Compressive Distributed Sparse Signal Recovery
(2018-01-01)
Wu, Jwo-Yuh
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Yang, Ming-Hsun
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Wang, Tsang-Yi
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電機工程學系
;
電信工程研究所
To strike a balance between energy efficiency and data quality control, this paper proposes a Neyman-Pearson type sensor censoring scheme for distributed sparse signal recovery via compressive-sensing based on wireless sensor networks. In the proposed approach, each sensor node employs a sparse sensing vector with known support for data compression, meanwhile enabling making local inference about the unknown support of the sparse signal vector of interest. This naturally leads to a ternary censoring protocol, whereby each sensor (i) directly transmits the real-valued compressed data if the sensing vector support is detected to be overlapped with the signal support, (ii) sends a one-bit hard decision if empty support overlap is inferred, (iii) keeps silent if the measurement is judged to be uninformative. Our design then aims at minimizing the error probability that empty support overlap is decided but otherwise is true, subject to the constraints on a tolerable false-alarm probability that non-empty support overlap is decided but otherwise is true, and a target censoring rate. We derive a closed-form formula of the optimal censoring rule; a low complexity implementation using bi-section search is also developed. Computer simulations are used to illustrate the performance of the proposed scheme.
A Sliding Window Approach for Dynamic Event-Region Detection in Sensor Networks
(2014-01-01)
Wang, Tsang-Yi
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Yang, Ming-Hsun
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Wu, Jwo-Yuh
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電機工程學系
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Department of Electrical and Computer Engineering
Event region detection is an important problem in wireless sensor networks. However, a fundamental assumption required for the event-region detection schemes proposed in the literature is that the event-region under detection is quasi-static, i.e., the event-regions do not change during the detection period. This assumption could fail in detecting fast varying events, such as forest fire events and mudslides. Therefore, the detection task considered in the present study is to cope with the continuously varying event regions. Specifically, we adopt a sliding window approach, in which only the sensor measurements from the present to a fixed length time ago are utilized for making decision at any particular time slot. Our simulation results demonstrate the advantages of the proposed detection scheme.
A Space-Time Fusion Scheme for Dynamic-Event Region Detection in Sensor Networks
(2016-01-01)
Wang, Tsang-Yi
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Yang, Ming-Hsun
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Wu, Jwo-Yuh
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電機工程學系
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Department of Electrical and Computer Engineering
Collaborative detection for continuously-varying event-region scenarios using wireless sensor networks (WSNs) has attracted much attention recently. However, most existing works adopt either a centralized approach, in which a powerful control center is used to reconstruct the entire random field, or a semi-centralized approach, in which extensive data exchange takes place among the sensors by means of real-value data communications. By contrast, the present study proposes a distributed dynamic event-region detection scheme for WSNs. The proposed scheme is based on a two-phase cooperative space-time decision fusion protocol. In Phase I, each sensor makes an initial decision in accordance with its Gaussian corrupted observation and previous decision. In Phase II, the nodes update their decisions in accordance with the decision information received from their neighboring nodes. The performance of the proposed scheme is compared with that of a semi-centralized detection scheme by means of computer simulations.
Achievable Angles Between Two Compressed Sparse Vectors Under Norm/Distance Constraints Imposed by the Restricted Isometry Property: A Plane Geometry Approach
(2013-04-01)
Chang, Ling-Hua
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Wu, Jwo-Yuh
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電機資訊學士班
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Undergraduate Honors Program of Electrical Engineering and Computer Science
The angle between two compressed sparse vectors subject to the norm/distance constraints imposed by the restricted isometry property (RIP) of the sensingmatrix plays a crucial role in the studies of many compressive sensing (CS) problems. Assuming that 1) u and v are two sparse vectors with (lambda) under bar (u, v) = theta and 2) the sensing matrix Phi satisfies RIP, this paper is aimed at analytically characterizing the achievable angles between Phi u and Phi v. Motivated by geometric interpretations of RIP and with the aid of the well-known law of cosines, we propose a plane-geometry-based formulation for the study of the considered problem. It is shown that all the RIP-induced norm/distance constraints on Phi u and Phi v can be jointly depicted via a simple geometric diagram in the 2-D plane. This allows for a joint analysis of all the considered algebraic constraints from a geometric perspective. By conducting plane geometry analyses based on the constructed diagram, closed-form formulas for the maximal and minimal achievable angles are derived. Computer simulations confirm that the proposed solution is tighter than an existing algebraic-based estimate derived using the polarization identity. The obtained results are used to derive a tighter restricted isometry constant of structured sensing matrices of a certain kind, to wit, those in the form of a product of an orthogonal projection matrix and a random sensing matrix. Follow-up applications in CS are also discussed.
Achievable Angles Between Two Compressed Sparse Vectors Under RIP-Induced Norm/Distance Constraints
(2014-01-01)
Chang, Ling-Hua
;
Wu, Jwo-Yuh
;
電機工程學系
;
Department of Electrical and Computer Engineering
The angle between two compressed sparse vectors subject to the norm/distance constraints imposed by the restricted isometry property (RIP) of the sensing matrix plays an important role in the studies of many compressive sensing (CS) problems. Assuming that (i) u and v are two sparse vectors with measured angle(u, v) = theta and (ii) the sensing matrix satisfies RIP, this paper is aimed at analytically characterizing the achievable angles between u and v. Motivated by geometric interpretations of RIP and with the aid of the well-known law of cosines, we propose a plane geometry based formulation for the study of the considered problem. It is shown that all the RIPinduced norm/distance constraints on u and v can be jointly depicted via a simple geometric diagram in the two-dimensional plane. This allows for a joint analysis of all the involved algebraic constraints from a geometric perspective. By conducting plane geometry analyses based on the constructed diagram, closedform formulae for the maximal and minimal achievable angles are derived. Computer simulations confirm that the proposed solution is tighter than an existing algebraic-based estimate derived using the polarization identity.
Achievable Throughput for Dual-Mode Limited-Feedback Transmit Beamforming over Temporally Correlated Wireless Channels
(2010)
Chang, Yi-Chieh
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Wu, Jwo-Yuh
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Lee, Ta-Sung
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電機工程學系
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Department of Electrical and Computer Engineering
Achieving high system throughput for limited-feedback communications against the time-varying channel effect is rather crucial in modern mobile system designs. Within the beamforming setup, this paper derives analytic throughput results for both the "more feedback less often" and "less feedback more often" scenarios. More specifically, under the assumptions that (i) the channels over two consecutive time slots follow the first-order Markov model and (ii) in each time slot, reliable feedback of a fixed amount of bits is allowed, the achievable system throughput over two consecutive time slots in both scenarios are characterized. In particular, while the exact throughput is in an integral form, we derive the associated closed-form approximate formulae which facilitate throughput evaluation without resorting to numerical integration. The analytic results also lead to a very low-complexity throughput-based mode selection scheme. Simulation study shows that: (1) the derived closed-form approximation is quite accurate; (2) with the aid of the proposed mode selection method, the throughput performance is robust against the channel temporal variation.
Amplitude-Aided 1-Bit Compressive Sensing Over Noisy Wireless Sensor Networks
(2015-10)
Chen, Ching-Hsien
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Wu, Jwo-Yuh
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電機學院
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College of Electrical and Computer Engineering
One-bit compressive sensing (CS) is known to be particularly suited for resource-constrained wireless sensor networks (WSNs). In this letter, we consider 1-bit CS over noisy WSNs subject to channel-induced bit flipping errors, and propose an amplitude-aided signal reconstruction scheme, by which 1) the representation points of local binary quantizers are designed to minimize the loss of data fidelity caused by local sensing noise, quantization, and bit sign flipping, and 2) the fusion center adopts the conventional l(1)-minimization method for sparse signal recovery using the decoded and de-mapped binary data. The representation points of binary quantizers are designed by minimizing the mean square error (MSE) of the net data mismatch, taking into account the distributions of the nonzero signal entries, local sensing noise, quantization error, and bit flipping; a simple closed-form solution is then obtained. Numerical simulations show that our method improves the estimation accuracy when SNR is low or the number of sensors is small, as compared to state-of-the-art 1-bit CS algorithms relying solely on the sign message for signal recovery.
An Enhanced Multi-Packet Reception MAC Protocol: Cooperative Approach
(2008)
Yang, Wen-Fang
;
Wu, Jwo-Yuh
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Lee, Ta-Sung
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電信工程研究所
;
Institute of Communications Engineering
An enhanced medium access control (MAC) protocol for wireless networks with multi-packet reception (MPR) capability is proposed. The proposed protocol is based on the dynamic multi-group priority queueing protocol recently introduced in [I] to exploit the cooperative diversity for improving the system throughput. Two kinds of throughput losses, i.e., over-loaded loss and under-loaded loss, are defined first to clarify the opportunity of improvement. it Markov chain analysis is provided as the theoretical background. It is shown that the under-loaded loss can be compensated by cooperation among users in light traffic environment, and the system throughput can be improved accordingly. Simulations further compare the delay and packet loss ratio with and without cooperation, it is found the average performance is improved too.
An Improved RIP-Based Performance Guarantee for Sparse Signal Reconstruction via Subspace Pursuit
(2014-01-01)
Chang, Ling-Hua
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Wu, Jwo-Yuh
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資訊工程學系
;
電機資訊學士班
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Department of Computer Science
Subspace pursuit (SP) is a well-known greedy algorithm capable of reconstructing a sparse signal vector from a set of incomplete measurements. In this paper, by exploiting an approximate orthogonality condition characterized in terms of the achievable angles between two compressed orthogonal sparse vectors, we show that perfect signal recovery in the noiseless case, as well as stable signal recovery in the noisy case, is guaranteed if the sensing matrix satisfies RIP of order 3K with RIC delta(3K) <= 0.2412. Our work improves the best-known existing results, namely, delta(3K) < 0.165 for the noiseless case [3] and delta(3K) < 0.139 when noise is present [4]. In addition, for the noisy case we derive a reconstruction error upper bound, which is shown to be smaller as compared to the bound reported in [4].
An Improved RIP-Based Performance Guarantee for Sparse Signal Reconstruction with Noise via Orthogonal Matching Pursuit
(2014-01-01)
Chang, Ling-Hua
;
Wu, Jwo-Yuh
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電信工程研究所
;
Institute of Communications Engineering
Stability of sparse signal reconstruction in the noisy case via orthogonal matching pursuit has been widely studied in the literature of compressive sensing. To guarantee exact support identification under l(2)/l(infinity) -norm bounded noise, sufficient conditions, characterized in terms of the restricted isometry constant and the minimum magnitude of the signal components, were reported in [2]. In this paper, we derive a less conservative set of sufficient conditions of the same kind. Our analyses exploit a newly developed "near-orthogonality" condition, which specifies the achievable angles between two compressed orthogonal sparse vectors. Thus, our improved performance guarantee benefits from more explicit knowledge about the geometry of the compressed space.
An Improved RIP-Based Performance Guarantee for Sparse Signal Recovery via Orthogonal Matching Pursuit
(2014-09-01)
Chang, Ling-Hua
;
Wu, Jwo-Yuh
;
電機工程學系
;
Department of Electrical and Computer Engineering
A sufficient condition reported very recently for perfect recovery of a K-sparse vector via orthogonal matching pursuit (OMP) in K iterations (when there is no noise) is that the restricted isometry constant (RIC) of the sensing matrix satisfies delta(K+1) < (1/root K + 1). In the noisy case, this RIC upper bound along with a requirement on the minimal signal entry magnitude is known to guarantee exact support identification. In this paper, we show that, in the presence of noise, a relaxed RIC upper bound delta(K+1) < (root 4K + 1 - 1/2K) together with a relaxed requirement on the minimal signal entry magnitude suffices to achieve perfect support identification using OMP. In the noiseless case, our result asserts that such a relaxed RIC upper bound can ensure exact support recovery in K iterations: this narrows the gap between the so far best known bound delta(K+1) < (1/root K + 1) and the ultimate performance guarantee delta(K+1) = (1/root K). Our approach relies on a newly established near orthogonality condition, characterized via the achievable angles between two orthogonal sparse vectors upon compression, and, thus, better exploits the knowledge about the geometry of the compressed space. The proposed near orthogonality condition can be also exploited to derive less restricted sufficient conditions for signal reconstruction in two other compressive sensing problems, namely, compressive domain interference cancellation and support identification via the subspace pursuit algorithm.
An Improved RIP-Based Performance Guarantee for Sparse Signal Recovery via Orthogonal Matching Pursuit
(2014-09-01)
Chang, Ling-Hua
;
Wu, Jwo-Yuh
;
交大名義發表
;
電機資訊學士班
;
National Chiao Tung University
A sufficient condition reported very recently for perfect recovery of a K-sparse vector via orthogonal matching pursuit (OMP) in K iterations (when there is no noise) is that the restricted isometry constant (RIC) of the sensing matrix satisfies delta(K+1) < (1/root K + 1). In the noisy case, this RIC upper bound along with a requirement on the minimal signal entry magnitude is known to guarantee exact support identification. In this paper, we show that, in the presence of noise, a relaxed RIC upper bound delta(K+1) < (root 4K + 1 - 1/2K) together with a relaxed requirement on the minimal signal entry magnitude suffices to achieve perfect support identification using OMP. In the noiseless case, our result asserts that such a relaxed RIC upper bound can ensure exact support recovery in K iterations: this narrows the gap between the so far best known bound delta(K+1) < (1/root K + 1) and the ultimate performance guarantee delta(K+1) = (1/root K). Our approach relies on a newly established near orthogonality condition, characterized via the achievable angles between two orthogonal sparse vectors upon compression, and, thus, better exploits the knowledge about the geometry of the compressed space. The proposed near orthogonality condition can be also exploited to derive less restricted sufficient conditions for signal reconstruction in two other compressive sensing problems, namely, compressive domain interference cancellation and support identification via the subspace pursuit algorithm.
BER Improved Transmit Power Allocation for D-STTD Systems with QR-Based Successive Symbol Detection
(2009)
Wu, Jwo-Yuh
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Kuang, Jie-Gang
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Lee, Ta-Sung
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電信工程研究所
;
Institute of Communications Engineering
We propose a BER improved power allocation scheme for D-STTD systems over i.i.d. Rayleigh fading channels under the OR-based successive detection framework. Instead of relying on BER under a fixed channel realization, the adopted design criterion is the mean BER (assuming there is no inter-layer error propagation) averaged with respect to the channel distribution. Such a design metric has two-fold advantages: (i) It is analytically tractable and is closely related to a block error probability upper pound when inter-layer error propagation occurs, and (ii) There is no need for repeated feedback of the instantaneous channel information. By exploiting a distinctive channel matrix structure unique to D-STTD systems we derive a closed-form approximate tipper bound of the considered BER metric; through minimization (if this bound an optimal power allocation scheme is obtained. Numerical simulation is used to illustrate the performance of the proposed method.
BER minimized power allocation for quasi-orthogonal space-time block coded signals with QR-based successive detection
(2007)
Wu, Jwo-Yuh
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Fan, Sheng-Po
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Kuang, Jie-Gang
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Lee, Ta-Sung
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電信工程研究所
We propose a minimal BER power allocation scheme for a class of quasi-orthogonal space-time block coded transmission (the so-called ABBA system) over i.i.d. Rayleigh fading channels under the QR-based successive detection framework. Instead of relying on BER under a fixed channel realization, the design criterion we adopt is the overall mean BER averaged with respect to the channel distribution. By exploiting a distinctive channel matrix structure induced by the ABBA code we derive a closed-form upper bound of the considered BER metric and, through minimization of which, an optimal power allocation scheme is obtained. Numerical simulation shows that the resultant performance is almost identical to that of the joint maximum-likelihood decoding in the medium-to-high SNR regime.
BER-Improved Quantization of Source-to-Relay Link SNR for Cooperative Beamforming: A Fixed Point Theory Approach
(2019-07-01)
Li, Wen-Hsuan
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Wu, Jwo-Yuh
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交大名義發表
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電信工程研究所
;
National Chiao Tung University
Cooperative beamforming is a potentially useful technique for enhancing link reliability in modern wireless relay communications. To aid the beamforming design, the signal-to-noise ratio (SNR) of the source-to-relay (S-R) channel links must be known at the destination node. Abdallah and Papadopoulos in IEEE Trans. Signal Processing, vol. 56, no. 10, 2008, proposed a beamforming system with relay-assisted SNR acquisition; that is, the S-R link SNR is first quantized at each relay and is then forwarded to the destination. An optimal quantizer design problem was proposed in that paper, aiming at reducing the system bit error rate; however, only the binary quantization case was considered therein, with the quantization threshold computed by a suggested rule of thumb. In this paper, we study the aforementioned quantizer design problem in the general multiple-bit setting. We show that the solutions to the first-order necessary condition for optimality can be obtained as a fixed point of a certain nonlinear map over the feasible threshold set. The existence and uniqueness of the fixed point are established by using, respectively, the Brouwer's and Schauder's fixed point theorems. Finally, we show that the fixed point thus obtained yields the globally optimal set of quantization thresholds. To the best of our knowledge, this paper is the first which leverages fixed point theories to rigorously solve SNR quantization problems in the context of wireless relay communication.
Blind channel estimation for single-carrier space-time block coded transmission with frequency-domain equalization: A diagonal precoding based approach
(2006)
Wu, Jwo-Yuh
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Lee, Ta-Sung
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電信工程研究所
;
Institute of Communications Engineering
Relying on non-redundant diagonal precoding and i.i.d. source assumption, we propose a blind channel estimation scheme for single-carrier frequency-domain equalization based space-time block coded systems. The proposed method exploits the precoding-induced linear signal structure in the conjugate cross-correlation between the two temporal block receive signals as well as the circulant channel matrix property, and can yield exact solutions whenever the channel noise is circularly Gaussian and the receive data statistic is perfectly obtained. The channel estimation formulation builds on rearranging the set of linear equations relating the entries of conjugate cross-correlation matrix and products of channel impulse responses into one with a distinctive block-circulant with circulant-block (BCCB) structure. This allows a simple identifiability condition depending on precoder parameters alone, and also provides a natural yet effective optimal precoder design framework against imperfect data estimation. We consider the data mismatch as a deterministic perturbation and propose to minimize the condition number of the BCCB system matrix, leading to a simple closed-form optimal solution. Numerical examples are used to illustrate the performance of the proposed method.