Closed-Form Approximation for the Performance of Finite Sample-Based Energy Detection Using Correlated Receiving Antennas

Nafkha, Amor; Aziz, Babar

doi:10.1109/lwc.2014.2348998

Cited by 19 publications

(18 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To examine the distribution of the random vector ̂, ( ) under both hypotheses, it is useful to invoke the partial test statistics, briefly (PTS), denoted as , . Such a PTS expression was manifested on ED algorithm in some recent studies [23,24], and it is also believed here that it resembles the local MTM-SVD approach given elsewhere [14]. So much as that and for one plausible interpretation, we can imagine the situation of having separate channel paths and each is loaded with samples of i.i.d.…”

Section: Decision Statisticsmentioning

confidence: 52%

Spectrum sensing in cognitive radio using multitaper method based on MIMO-OFDM techniques

et al. 2019

View full text Add to dashboard Cite

The current inefficient utilization of frequency spectrum has alerted regulatory bodies to streamline improvements. Cognitive radio (CR) has recently received considerable attention and is widely perceived as a promising improvement tool in estimating, or equivalently sensing, the frequency spectrum for wireless communication systems. The cognitive cycle in CR systems is capable of recognizing and processing better spectrum estimation (SE) and hence promotes the efficiency of spectrum utilization. Among different SE methods, the multi-taper method (MTM) shows encouraging results. Further performance improvement in the SE for CR can be achieved by applying multiple antennas and combining techniques. This paper proposes a constructive development of SE using MTM, abbreviated as MTSE, and by employing multiple-input multiple-output (MIMO), parsed into separate parallel channels using singular value decomposition (SVD), and maximum ratio combining (MRC) configurations. Deviating from these improvements, however, multicarrier systems such as orthogonal frequency division multiplexing (OFDM) show inferior sensing performances due to the noise multiplicity generated and combined from all subcarrier channels. By means of the quadrature matrix form, the probabilities for such integrated settings of SE have been derived to reach at their approximate asymptotes. Numerical simulations revealed specific better performances stemmed from coupling the fashionable MTSE and MIMO technologies.

show abstract

Section: Decision Statisticsmentioning

confidence: 52%

Spectrum sensing in cognitive radio using multitaper method based on MIMO-OFDM techniques

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Further, the throughput under CSS scenario (R c ) is computed by simply replacing the P f with Q f and P d with Q d in Equation (13). (6) and λ e from (8) and (9) for Rayleigh and Nakagami-m fading channels, respectively. Moreover, the proposed algorithm's flowchart is also presented with Figure 2.…”

Section: Css and Throughput Computationmentioning

confidence: 99%

“…Moreover, the proposed algorithm's flowchart is also presented with Figure 2. (8) and (9) for Rayleigh and Nakagami-m fading channels, respectively. 4.…”

Section: Css and Throughput Computationmentioning

confidence: 99%

“…[1][2][3][4] The cognitive radio network (CRN) follows the OSA model in which the cognitive user (CU) periodically senses the spectrum to identify the free/unused channels in specified radio frequency (RF) environment. Among the variety of spectrum sensing techniques available in the reported literature, 7 the energy detector spectrum sensing (EDSS) 8,9 technique is most widespread due to its least complexity among all other available spectrum sensing techniques used in cognitive radio communication systems, and also, its practical implementation is convenient. Among the variety of spectrum sensing techniques available in the reported literature, 7 the energy detector spectrum sensing (EDSS) 8,9 technique is most widespread due to its least complexity among all other available spectrum sensing techniques used in cognitive radio communication systems, and also, its practical implementation is convenient.…”

Section: Introductionmentioning

confidence: 99%

“…5,6 An efficient and accurate functioning of the spectrum sensing is one of the most important requirements of the CUs in the cognitive radio communication technology. Among the variety of spectrum sensing techniques available in the reported literature, 7 the energy detector spectrum sensing (EDSS) 8,9 technique is most widespread due to its least complexity among all other available spectrum sensing techniques used in cognitive radio communication systems, and also, its practical implementation is convenient. 7 The key metrics to measure the sensing performance of EDSS are the probability of false alarm (P f ), probability of detection (P d ), and error probability (P e ), which are affected mainly by the selection of predefined threshold value.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Intelligent threshold selection in fading environment of cognitive radio network: Advances in throughput and total error probability

Kumar

Thakur

Pandit

et al. 2019

Int J Communication

View full text Add to dashboard Cite

One of the main challenges of spectrum sensing (SS) in the cognitive radio network (CRN) is selection of threshold for captivating the sensing decision, and such an issue becomes more challenging especially at low signal-to-noise ratio (SNR) because it affects the sensing performance and throughput of cognitive user (CU). However, the sensing decision of individual CU may not be accurate due to fading effects in the sensing environment, and significant improvement is accomplished with the cooperation of users. Therefore, in this paper, we have investigated the performance of energy detector SS (EDSS) technique in the CRN under fading environment with cooperative and noncooperative SS scenario. Further, we have introduced the concept of critical SNR (γ c ) to select the appropriate threshold and based on which the algorithms are proposed to enhance the throughput and reduce the total error (sensing error) probability of CU at different SNR (γ). From the results, we have accomplished that at the low SNR region (γ ≤ γ c ), throughput is maximum with constant false-alarm rate (CFAR) threshold selection approach in the cooperative scenario while in the high SNR region (γ > γ c ), its value is maximum with minimizing the error probability (MEP) threshold selection approach in the noncooperative scenario. Moreover, the sensing error is reduced with cooperation, and threshold selection with MEP approach outperforms CFAR approach for γ ≤ γ c . Further, the proposed approach outperforms the other approaches in terms of throughput and sensing error (total error) probability in the Rayleigh and Nakagami-m fading environments.

show abstract

Analysis of optimal threshold selection for spectrum sensing in a cognitive radio network: an energy detection approach

et al. 2019

View full text Add to dashboard Cite

Closed-Form Approximation for the Performance of Finite Sample-Based Energy Detection Using Correlated Receiving Antennas

Cited by 19 publications

References 10 publications

Spectrum sensing in cognitive radio using multitaper method based on MIMO-OFDM techniques

Spectrum sensing in cognitive radio using multitaper method based on MIMO-OFDM techniques

Intelligent threshold selection in fading environment of cognitive radio network: Advances in throughput and total error probability

Analysis of optimal threshold selection for spectrum sensing in a cognitive radio network: an energy detection approach

Contact Info

Product

Resources

About