Performance Analysis of Distributed Decision Fusion Using A Multilevel Censoring Scheme in Wireless Sensor Networks

Cheng, Victor W.; Wang, Tsang-Yi

doi:10.1109/tvt.2012.2187467

Cited by 17 publications

(15 citation statements)

References 25 publications

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“…The FIM I(q 0 ) is obtained from equation (17). Similar to the steps in the proof in Proposition 1, we can show that I j, k (q 0 ) = 0 if j 6 ¼ k. For j = k = m, from equations (19) and (33), we have…”

Section: The Rao Test Fusion Rulel R Is Derived From Equationmentioning

confidence: 71%

“…17 Therefore, many transmission strategies have been proposed to spend energy efficiently. For example, the sensor-censoring strategy 18,19 suggests that only reliable (uncensored) local decisions should be transmitted to the FC and the ordered-transmission strategy 20,21 further points out that transmitting local decisions in order of their reliabilities will help saving both the energy and the collection time. Note that the collection time is the time duration that the FC spends to collect local decisions.…”

Section: Introductionmentioning

confidence: 99%

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Decision fusion for composite hypothesis testing in wireless sensor networks over a shared and noisy collision channel

Laitrakun

2020

International Journal of Distributed Sensor Networks

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We consider the composite hypothesis testing problem of time-bandwidth-constrained distributed detection. In this scenario, the probability distribution of the observed signal when the event of interest is happening is unknown. In addition, local decisions are censored and only those uncensored local decisions will be sent to the fusion center over a shared and noisy collision channel. The fusion center also has a limited time duration to collect transmitted decisions and make a final decision. Two types of medium access control that the sensor nodes apply to send their decisions are investigated: time division multiple access and slotted-Aloha. Unlike using the time division multiple access protocol, the slotted-Aloha-based distributed detection will experience packet collisions. However, in this article, since only uncensored decisions are sent, packet collisions are informative. We derive fusion rules according to generalized likelihood ratio test, Rao test, and Wald test for both the time division multiple access–based distributed detection and the slotted-Aloha-based distributed detection. We see that the fusion rules for the slotted-Aloha-based distributed detection here also exploit packet collisions in the final decision-making. In addition, the asymptotic performances and energy consumption of both schemes are analyzed. Extensive simulation and numerical results are provided to compare the performances of these two schemes. We show that, for a given time delay, the slotted-Aloha-based distributed detection can outperform the time division multiple access–based distributed detection by increasing the number of sensor nodes which results in higher energy consumption.

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Section: The Rao Test Fusion Rulel R Is Derived From Equationmentioning

confidence: 71%

Section: Introductionmentioning

confidence: 99%

Decision fusion for composite hypothesis testing in wireless sensor networks over a shared and noisy collision channel

Laitrakun

2020

International Journal of Distributed Sensor Networks

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“…A multi-level decision algorithm is applied on the observation at each sensor [24,25,26], where W l at the l-th sensor is divided into M equally spacing regions as shown in Figure 1.…”

Section: -Ary Signalingmentioning

confidence: 99%

Distributed Decision Fusion with M-ary Signaling and k-bit Transmission on Sensor Observation in Wireless Sensor Networks

Cheng¹,

Wang²

2021

IJICS

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Multi-level decisions on sensor detection is able to improve the detection performance on the final decision made at the fusion center (FC) in wireless sensor networks (WSN). In this paper, the performance analysis of an M -ary signaling (MS) scheme using analog transmission and a k-bit transmission (KB) scheme is both examined for distributed binary detection. Under the multi-level decision algorithms, each sensor sends a signal carrying the information of a quantized version of a local decision statistic such as the conditional mean or the log-likelihood ratio. In MS, the output of the quantizer is transmitted directly without digitalizing and coding process, while in KB, each quantization output is coded with k bits and hereby a sensor sends a k-bit hard local decision to the FC. At the FC, the linear combiner detection rule on the transmission schemes is both adopted to make the final decision. The effects of the sensor decision and the transmission errors are incorporated in the analysis of the erroneous performance of the final decision. The goal of the proposed schemes is to minimize the final errors at the FC via optimizing the region allocation on the multi-level decision at the sensor. The numerical results illustrate that the proposed schemes achieve significant improvement in error performance over the conventional schemes under either additive white Gaussian noise (AWGN) channel or Rayleigh faded channel.

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“…A prevailing model used for such applications is the orthogonal multi-access channel (MAC) model wherein sensors make local decisions based on their observations and subsequently transmit these decisions in parallel to a fusion center (FC). Numerous researchers have focused on the problem of distributed detection (decision fusion) over orthogonal MACs [10,11,12,13,14,15,16,17,18,19,20,21].…”

Section: Introductionmentioning

confidence: 99%

Noncoherent Decision Fusion over Fading Hybrid MACs in Wireless Sensor Networks

Liu

Wang

Liu

et al. 2019

Sensors

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In this paper, we consider the problem of decision fusion for noncoherent detection in a wireless sensor network. Novel to the current work is the integration of the hybrid multi-access channel (MAC) in the fusion rule design. We assume that sensors transmit their local binary decisions over a hybrid MAC which is a composite of conventional orthogonal and nonorthogonal MACs. Under Rayleigh fading scenario, we present a likelihood ratio (LR)-based fusion rule, which has been shown to be optimal through theoretical analysis and simulation. However, it requires a large amount of computation, which is not easily implemented in resource-constrained sensor networks. Therefore, three sub-optimal alternatives with low-complexity are proposed, namely the weighed energy detector (WED), the deflection-coefficient-maximization (DCM), and the two-step (TS) rules. We show that when the channel signal-to-noise ratio (SNR) is low, the LR-based fusion rule reduces to the WED rule; at high-channel SNR, it is equivalent to the TS rule; and at moderate-channel SNR, it can be approached closely by the DCM rule. Compared with the conventional orthogonal and nonorthogonal MACs, numerical results show that the hybrid MAC with the proposed fusion rules can improve the detection performance when the channel SNR is medium.

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Performance Analysis of Distributed Decision Fusion Using A Multilevel Censoring Scheme in Wireless Sensor Networks

Cited by 17 publications

References 25 publications

Decision fusion for composite hypothesis testing in wireless sensor networks over a shared and noisy collision channel

Decision fusion for composite hypothesis testing in wireless sensor networks over a shared and noisy collision channel

Distributed Decision Fusion with M-ary Signaling and k-bit Transmission on Sensor Observation in Wireless Sensor Networks

Noncoherent Decision Fusion over Fading Hybrid MACs in Wireless Sensor Networks

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