Cooperative Spectrum Sensing in Cognitive Radio Networks with Weighted Decision Fusion Schemes

Peh, Edward; Liang, Ying‐Chang; Guan, Yong Liang; Zeng, Yonghong

doi:10.1109/twc.2010.092810.100320

Cited by 98 publications

(73 citation statements)

References 17 publications

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“…In such methods, the spectrum availability information obtained from multiple SUs can also be processed using more sophisticated techniques. Instances include weighting [9], multidimensional correlation [10] and minimizing the collision probability at the PUs [5]. In weighting, the share of the provided information by each sensor in the final decision is determined by a weighting vector which is a system design parameter.…”

Section: Introductionmentioning

confidence: 99%

A Low-Latency Zone-Based Cooperative Spectrum Sensing

Deepak

Navaie

2016

IEEE Sensors J.

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Abstract-In this paper we propose a spectrum sensing scheme for wireless systems with low latency requirement such as machine-to-machine communications. In such systems with high spatial density of the base stations and users/objects, spectrum sharing enables spectrum reuse across very small regions. This however needs efficient incorporation of sensors' location information into spectrum sensing. We propose a multi-channel cooperative spectrum sensing technique in which an independent network of sensors, namely monitoring network, detects the spectrum availability. The monitoring network divides the coverage area into overlapped but independent zones. This enables exploiting high spatial distribution without incorporating exact sensors' location. Corresponding to each zone, a zone aggregator (ZA) is introduced which processes the sensors' output. The aggregated decision in each zone associated with the ZA's location is then passed to a decision fusion center (DFC). The secondary base station (SBS) accordingly allocates the available channels to maximize the spectral efficiency. We formulate the function of the DFC as an optimization problem with the objective of maximizing the spectral efficiency. For energy detector sensors, we further obtain optimal detection threshold for different cases with various spatial densities of ZAs and SBSs. This provides extra degrees of freedom in designing the spectrum monitoring network and provides quantitative insight on network design. We further devise an efficient protocol for the proposed technique with very low signaling complexity and show that the proposed method reduces the spectrum sensing latency and results in a higher spectrum efficiency. Extensive simulations confirm our analytical results and indicate a significant improvement in sensing latency and accuracy.

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Section: Introductionmentioning

confidence: 99%

A Low-Latency Zone-Based Cooperative Spectrum Sensing

Deepak

Navaie

2016

IEEE Sensors J.

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“…fading channels by increasing the number of the cooperating SUs, while at the same time protecting the PUs in the environment from the harmful interference induced by these SUs [3]. Furthermore, several decision combining algorithms for the cooperating SUs were studied in [4] and [5] as well.…”

Section: Introductionmentioning

confidence: 99%

Effective capacity in cognitive radio broadcast channels

Hammouda

Akın

Peissig

2014

2014 IEEE Global Communications Conference

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Abstract-In this paper, we investigate effective capacity by modeling a cognitive radio broadcast channel with one secondary transmitter (ST) and two secondary receivers (SRs) under quality-of-service constraints and interference power limitations. We initially describe three different cooperative channel sensing strategies with different hard-decision combining algorithms at the ST, namely OR, Majority, and AND rules. Since the channel sensing occurs with possible errors, we consider a combined interference power constraint by which the transmission power of the secondary users (SUs) is bounded when the channel is sensed as both busy and idle. Furthermore, regarding the channel sensing decision and its correctness, there exist possibly four different transmission scenarios. We provide the instantaneous ergodic capacities of the channel between the ST and each SR in all of these scenarios. Granting that transmission outage arises when the instantaneous transmission rate is greater than the instantaneous ergodic capacity, we establish two different transmission rate policies for the SUs when the channel is sensed as idle. One of these policies features a greedy approach disregarding a possible transmission outage, and the other favors a precautious manner to prevent this outage. Subsequently, we determine the effective capacity region of this channel model, and we attain the power allocation policies that maximize this region. Finally, we present the numerical results. We first show the superiority of Majority rule when the channel sensing results are good. Then, we illustrate that a greedy transmission rate approach is more beneficial for the SUs under strict interference power constraints, whereas sending with lower rates will be more advantageous under loose interference constraints. Finally, we note that the methodology and the approach we consider in this study can be easily applied into a more general cognitive radio broadcast channel model with more than two SRs.

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“…The case that SUs have different detection SNRs has been considered in [10], and local decisions are weighted based on the likelihood-ratio-test (LRT) at the FC. Detection performance of CSS affected by both multipath fading and shadowing has been investigated in [11].…”

Section: Introductionmentioning

confidence: 99%

A trust-based method for cooperative spectrum sensing in cognitive radio networks

Shu

Wang

Liu

et al. 2013

2013 3rd International Conference on Consumer Electronics, Communications and Networks

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Cognitive radio has been treated as a promising candidate for reusing underutilized or unused spectrum resources of licensed users without interference to licensed users by means of opportunistic spectrum access. Reliable spectrum sensing is one of foundational techniques for cognitive users to detect spectrum holes and monitor licensed users' activities in cognitive radio. However, many factors make it much difficult for single cognitive user to accurately and rapidly identify the activity status of licensed users, such as very low signal-to-noise ratio, and noise uncertainty, and fading, and shadowing, and quite short sensing time, etc. In this paper, we proposed a weighted scheme for cooperative spectrum sensing considering trust factor of each collaborative user to improve the global sensing performance in cognitive radio networks. The cognitive users performed spectrum sensing using energy detectors and transmitted their binary local decisions as well as binary information on the success or failure in previous data transmission to the fusion center for a global decision based weighted decision fusion on the absence or presence of the licensed users' activities. Weighted values depended on trust factors of corresponding cognitive users. Simulation results showed that the proposed method can efficiently overcome the influence of the aforementioned negative factors.

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Cooperative Spectrum Sensing in Cognitive Radio Networks with Weighted Decision Fusion Schemes

Cited by 98 publications

References 17 publications

A Low-Latency Zone-Based Cooperative Spectrum Sensing

A Low-Latency Zone-Based Cooperative Spectrum Sensing

Effective capacity in cognitive radio broadcast channels

A trust-based method for cooperative spectrum sensing in cognitive radio networks

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