Estimation of Primary Channel Activity Statistics in Cognitive Radio Based on Imperfect Spectrum Sensing

Toma, Ogeen H.; López-Benítez, Miguel; Patel, Dhaval; Umebayashi, Kenta

doi:10.1109/tcomm.2020.2965944

Cited by 40 publications

(44 citation statements)

References 36 publications

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“…In simulations, as input parameters of the algorithm, m init and λ msw are set as 1% and 5% of the observation window, respectively. As the basic reference method, we study the estimation of primary user activity based on the idle/busy periods determined by using short spectrum sensing decisions [12,13,17]. As the above method, however, requires noise floor information, which we obtain using the extended Forward Consecutive Mean Excision (FCME) algorithm with Welch FFT [13,17].…”

Section: Simulation Setup and Resultsmentioning

confidence: 99%

“…We evaluate the algorithm in terms of signal samples detection and complete samples recognition with respect to SNR and different PU activity factors, and also examine the execution time of the detection process. Besides, its performance is compared with the well-known reference methods in the literature [ 12 , 13 , 14 ], which is then followed by its utility appraisal for channel occupancy estimation. To assess the accuracy of these operations, a semi-experimental simulation setup of packet-based PU transmission is designed, where the background distortion comes from the radio frequency (RF) noise traces captured with National Instrument software defined radio (SDR), USRP-2900.…”

Section: Introductionmentioning

confidence: 99%

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A Blind Signal Samples Detection Algorithm for Accurate Primary User Traffic Estimation

Nikonowicz

Mahmood

Gidlund

2020

Sensors

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The energy detection process for enabling opportunistic spectrum access in dynamic primary user (PU) scenarios, where PU changes state from active to inactive at random time instances, requires the estimation of several parameters ranging from noise variance and signal-to-noise ratio (SNR) to instantaneous and average PU activity. A prerequisite to parameter estimation is an accurate extraction of the signal and noise samples in a received signal time frame. In this paper, we propose a low-complexity and accurate signal samples detection algorithm as compared to well-known methods, which is also blind to the PU activity distribution. The proposed algorithm is analyzed in a semi-experimental simulation setup for its accuracy and time complexity in recognizing signal and noise samples, and its use in channel occupancy estimation, under varying occupancy and SNR of the PU signal. The results confirm its suitability for acquiring the necessary information on the dynamic behavior of PU, which is otherwise assumed to be known in the literature.

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Section: Simulation Setup and Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Blind Signal Samples Detection Algorithm for Accurate Primary User Traffic Estimation

Nikonowicz

Mahmood

Gidlund

2020

Sensors

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“…It is worth mentioning that the existing Wi-Fi activity statistics can be estimated by the LTE system without any coordination between the coexisting networks and this can be performed based on the energy detection sensing decisions of the LAA algorithm [12], [44], [45]. In particular, LAA eNB can periodically sense the Wi-Fi channel state when LAA is not transmitting to estimate the Wi-Fi ON time periods.…”

Section: A Dynamic Cw (Dyncw) Methodsmentioning

confidence: 99%

Novel LAA Waiting and Transmission Time Configuration Methods for Improved LTE-LAA/Wi-Fi Coexistence Over Unlicensed Bands

Alhulayil

López-Benítez

2020

IEEE Access

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Long Term Evolution-Licensed Assisted Access (LTE-LAA) has been pointed out as a key solution to cope with the increasing amounts of data traffic and the scarcity of the licensed spectrum. The 3rd Generation Partnership Project (3GPP) has standardised LAA to operate over the 5 GHz unlicensed spectrum which is mainly occupied by Wi-Fi. It is a challenging problem to ensure a fair coexistence between these technologies. Several studies have been proposed in the literature to allow a fair LAA/Wi-Fi coexistence. In this work, various methods are proposed to adapt/select the waiting times for LAA based on the activity statistics of the existing Wi-Fi network. The main novelty is that the knowledge of the existing Wi-Fi activities is exploited to tune the boundaries of the Contention Window (CW) for LAA and to select fixed waiting times for LAA. Moreover, a dynamic method is proposed to adapt the Transmission Opportunity (TxOP) times for LAA based on the Hybrid Automatic Repeat Request (HARQ) feedbacks. The methods are evaluated using ns-3 network simulator based on the 3GPP fairness definition. We show that selecting fixed waiting times for LAA based on the existing Wi-Fi activities is more friendly to the existing Wi-Fi and provides better total aggregated throughputs for both coexisting networks compared to the 3GPP Category 4 Listen Before Talk (Cat 4 LBT) algorithm. Moreover, the proposed dynamic TxOP method is more friendly to the existing Wi-Fi and provides better total aggregated throughputs compared to the fixed TxOP period approach of the 3GPP Cat 4 LBT scheme. INDEX TERMS Licensed assisted access, LTE/Wi-Fi coexistence, ns-3, Unlicensed spectrum, Wi-Fi.

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“…Cognitive Radio (CR) solutions provide a highly attractive communication technology to access the underutilized frequency bands. This enabling technology opens up the licensed spectrum bands to the unlicensed Secondary Users (SUs) (Toma et al, 2020). SUs are allowed to sense, observe, and learn from the environment to opportunistically access underutilized frequency bands of licensed Primary Users (PUs) (Akyildiz and Brandon, 2011).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-based reliable and secure cooperative spectrum sensing for the smart grid

Nassef¹,

Alhebshi²

2021

Int. j. adv. appl. sci.

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Cognitive radio is a promising technology to solve the spectrum scarcity problem caused by inefficient utilization of radio spectrum bands. It allows secondary users to opportunistically access the underutilized spectrum bands assigned to licensed primary users. The local individual spectrum detection is inefficient, and cooperative spectrum sensing is employed to enhance spectrum detection accuracy. However, cooperative spectrum sensing opens up opportunities for new types of security attacks related to the cognitive cycle. One of these attacks is the spectrum sensing data falsification attack, where malicious secondary users send falsified sensing reports about spectrum availability to mislead the fusion center. This internal attack cannot be prevented using traditional cryptography mechanisms. To the best of our knowledge, none of the previous work has considered both unreliable communication environments and the spectrum sensing data falsification attack for cognitive radio based smart grid applications. This paper proposes a fuzzy inference system based on four conflicting descriptors. An attack model is formulated to determine the probability of detection for both honest and malicious secondary users. It considers four independent malicious secondary users’ attacking strategies of always yes, always no, random, and opposite attacks. The performance of the proposed fuzzy fusion system is simulated and compared with the conventional fusion rules of AND, OR, Majority, and the reliable fuzzy fusion that does not consider the secondary user’s sensing reputation. The results indicate that incorporating sensing reputation in the fusion center has enhanced the accuracy of spectrum detection and have prevented malicious secondary users from participating in the spectrum detection fusion

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Estimation of Primary Channel Activity Statistics in Cognitive Radio Based on Imperfect Spectrum Sensing

Cited by 40 publications

References 36 publications

A Blind Signal Samples Detection Algorithm for Accurate Primary User Traffic Estimation

A Blind Signal Samples Detection Algorithm for Accurate Primary User Traffic Estimation

Novel LAA Waiting and Transmission Time Configuration Methods for Improved LTE-LAA/Wi-Fi Coexistence Over Unlicensed Bands

Fuzzy-based reliable and secure cooperative spectrum sensing for the smart grid

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