SNR Walls for Signal Detection

Tandra, Rahul; Sahai, Anant

doi:10.1109/jstsp.2007.914879

Cited by 1,309 publications

(893 citation statements)

References 18 publications

(18 reference statements)

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“…The fundamental limitations in energy detection found in this paper based on the constraint Equation (1) are different from the SNR wall introduced in [16], which is on the other hand a limitation regarding robustness of detectors. It is discovered in this paper that even when the noise variance keeps constant, some limitations still exist regarding the tradeoff between efficiency and noninterference.…”

Section: Introductionmentioning

confidence: 69%

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Fundamental Limitations in Energy Detection for Spectrum Sensing

Peng

2018

JSAN

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Abstract:A key enabler for Cognitive Radio (CR) is spectrum sensing, which is physically implemented by sensor and actuator networks typically using the popular energy detection method. The threshold of the binary hypothesis for energy detection is generally determined by using the principles of constant false alarm rate (CFAR) or constant detection rate (CDR). The CDR principle guarantees the CR primary users at a designated low level of interferences, which is nonetheless subject to low spectrum usability of secondary users in a given sensing latency. On the other hand, the CFAR principle ensures secondary users' spectrum utilization at a designated high level, while may nonetheless lead to a high level of interference to the primary users. The paper introduces a novel framework of energy detection for CR spectrum sensing, aiming to initiate a graceful compromise between the two reported principles. The proposed framework takes advantage of the summation of the false alarm probability P f a from CFAR and the missed detection probability (1 − P d ) from CDR, which is further compared with a predetermined confidence level. Optimization presentations for the proposed framework to determine some key parameters are developed and analyzed. We identify two fundamental limitations that appear in spectrum sensing, which further define the relationship among the sample data size for detection, detection time, and signal-to-noise ratio (SNR). We claim that the proposed framework of energy detection yields merits in practical policymaking for detection time and design sample rate on specific channels to achieve better efficiency and less interferences.

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Section: Introductionmentioning

confidence: 69%

“…(ii) By taking σ 2 n and M fixed, we target to find minimum SNR and corresponding threshold λ satisfying the inequality in Equation (16). This also results in a nonlinear optimization problem as following:…”

Section: Thresholds By New Principlementioning

confidence: 99%

Fundamental Limitations in Energy Detection for Spectrum Sensing

Peng

2018

JSAN

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“…The timing and sensitivity requirements are in direct conflict with each other as increasing the sensing time improves sensitivity [10]. However, the 4µs limit is a hard limit imposed by the standard and therefore we will strive to achieve the needed sensitivity within the standard defined times.…”

Section: Constrai Ntsmentioning

confidence: 99%

“…Filtering the received signal with a matched filter before performing the detection (figure 5) will increase the sensitivity [10]. Given complete a priori knowledge of the modulation scheme, this filter corresponds to the receive filter used for demodulation and will provide the best possible detection rate.…”

Section: Fig 4 Simple Energy Detection Architecturementioning

confidence: 99%

Coexistence Aware Clear Channel Assessment

Valck

Tytgat

Moerman

et al. 2013

Lecture Notes in Computer Science

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Abstract. Wireless sensor networks are used by an ever growing number of applications which have ever increasing Quality of Service requirements. The available unlicensed industrial scientific and medical bands -where wireless sensor networks typically operate -are crowded with a number of technologies interfering with each other. Delivering a sufficiently high QoS within these frequency bands is therefore becoming more and more difficult. A theoretic concept named Coexistence Aware Clear Channel Assessment (CACCA) promises more reliable QoS when different technologies utilize the same. Within this paper we propose two methods to perform CACCA and create an SDR prototype to show that CACCA can achieve a high packet error rate reduction in an IEEE 802.15.4 network when it coexists with IEEE 802.11.

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“…The matched filter has a requirement of fewer signal samples, which grows as (1 / SNR) O for a target probability of false alarm at low SNRs [36,37]. Thus, there exists a SNR wall for a matched filtering method [38]. Moreover, matched filter detection requires that the received signals are demodulated.…”

Section: Spectrum Sensingmentioning

confidence: 99%

Intelligent and efficient development of wireless networks: A review of cognitive radio networks

et al. 2012

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Facing the challenges on how to improve spectrum efficiency and how to realize heterogeneous network convergence in future wireless networks, a cognitive radio network (CRN) is proposed as one of the solutions. This has become a major research topic in recent years and it is timely to give an overview of the development of CRN and to summarize key issues and technologies. The fundamental concepts of CRN, including the cognitive cycle model, the network architecture, and the cognitive ability and intelligent decision functions, are introduced in detail based on recent advances. Key issues for each topic, followed with recent research on theory and method, are then classified and the industrialization developments of CRN testbeds based on TD-LTE cellular system and standards are briefly presented. Finally, conclusions are reached on the perspectives and directions of future development.cognitive radio networks, network architecture, cognitive ability, spectrum sensing, intelligent decision and dynamic spectrum allocation, end-to-end performance Driven by the requirements of ubiquitous wireless access and personalized wireless applications [1], worldwide, numerous wireless technologies are invading our lives, such as evolutionary telecommunication technologies, wideband wireless access and short distance wireless technologies. Furthermore, the concept of the internet of things (IoT) has become widespread based on the development of wireless sensor networks. With the explosive development of wireless technologies, several challenges must be addressed. The electromagnetic spectrum, whose use is licensed and managed by government, has been scarce for allocation to ubiquitous wireless applications. However, contrary to the physical scarcity of the available spectrum, the report published by the federal communication commission (FCC) shows that over 60 % of the licensed spectrum below 6 GHz remains underused [2,3]. The measurement results in Figure 1 taken in Beijing over a one month period, also indicate low spectrum use consistent with the results released by the FCC. Therefore, improvement of spectrum efficiency is the first challenge to be examined. On the other hand, the end-to-end performance of wireless networks is considered to be the performance indicator for ubiquitous and personalized wireless applications [4], such as end-to-end throughput, end-to-end delay and routing scheme, which take into account all network elements in a data transmission flow across different layers for the global optimization from the network aspect. Because the property of heterogeneity causes low radio resource use and mutual interference among heterogeneous networks, the other big challenge is that heterogeneous network convergence is needed to improve the end-to-end performance of wireless networks.Cognitive radio (CR), proposed by Mitola in 1999 [5,6], is considered a feasible solution for improving spectrum efficiency. Furthermore, a cognitive radio network (CRN), which is defined as a wireless network with the capabilities

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SNR Walls for Signal Detection

Cited by 1,309 publications

References 18 publications

Fundamental Limitations in Energy Detection for Spectrum Sensing

Fundamental Limitations in Energy Detection for Spectrum Sensing

Coexistence Aware Clear Channel Assessment

Intelligent and efficient development of wireless networks: A review of cognitive radio networks

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