Throughput analysis of cooperative cognitive radio network over generalized κ–μ and η–μ fading channels

Balam, Suresh Kumar; Siddaiah, P.; Nallagonda, Srinivas

doi:10.1007/s11276-018-1758-4

Cited by 15 publications

(6 citation statements)

References 31 publications

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“…In [26], throughput maximisation of a secondary network is studied, considering HDCSs at the FC, in the presence of η − μ and κ − μ fading environments. Finally, obtaining new expressions for all SDCSs and investigating the performance of CSS in a generalised fading environment can be a significant work for the researchers for the next 5G-or 6G-based wireless networks.…”

Section: Background Workmentioning

confidence: 99%

Comprehensive performance analysis of data‐fusion aided cooperative cognitive radio network over η − μ fading channel

Nallagonda¹,

Kumar²,

Nallagonda³

2019

IET Communications

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Section: Background Workmentioning

confidence: 99%

Comprehensive performance analysis of data‐fusion aided cooperative cognitive radio network over η − μ fading channel

Nallagonda¹,

Kumar²,

Nallagonda³

2019

IET Communications

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“…Each CR senses a PU and sends sensing information (energy) without performing local decision to the FC via reporting channels. The signal received at

j th

CR,

y_{j} false(t false) false(j \in falsefalse{1 \dots M falsefalse} false)

, can be written as

\begin{matrix} right leftthickmathspace.5em \\ y_{j} (t) = \{\begin{matrix} 1em4pt \\ n_{j} (t) 00 & H_{0}, \\ h_{j} s (t) + n_{j} (t) & H_{1} . \end{matrix} \end{matrix}

In [3], the expressions of an average

P_{d, j}

{\bar{P}}_{d, j}

for a single CR are derived under

κ - μ

and

η - μ

channels. The

Q_{d}^{G N}

expression of each SLS, SLC, MRC, and SC scheme in AWGN channels is given in [5], and an average

Q_{d}

{\bar{Q}}_{d}

for a given SDF scheme can be derived as

{\bar{Q}}_{d} = \int_{0}^{\infty} Q_{d}^{G N} f_{γ} false(γ_{s} false) d γ_{s},

where

f_{γ} false(γ_{s} false)

is the probability density function of

…”

Section: Network Modelmentioning

confidence: 99%

“…In a practical wireless communication system, it is not possible to make an accurate decision about a PU by a single CR due to the presence of severe shadowing or fading. In such case, a cooperative spectrum sensing scheme is performed at fusion centre (FC) to take an accurate decision about PU [3]. Different cooperative schemes, namely, hard‐decision fusion (HDF) and soft data fusion (SDF) schemes are developed at FC [4].…”

Section: Introductionmentioning

confidence: 99%

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Data fusion‐aided cognitive radio network over generalised fading channels

Nallagonda¹

2019

Electron. lett.

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In this Letter, the authors study analytical performance of various soft data fusion (SDF) schemes over generalised fading channels in a cognitive radio network. Two generalised fading models, namely, k − m and h − m are considered individually in the sensing channels and various SDF techniques are implemented at the fusion centre. Novel analytical frameworks for cooperative detection probability are developed subject to SDF and generalised fading and validated through computer simulations. Optimal values of the detection thresholds are determined where an average error rate is minimum.

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“…In IED, decision statistic is measured by considering a power operation on the amplitude of the received signal with properly optimized positive exponent 16‐19 . In Balam et al, 20 CED‐based CSS system is used to investigate throughput performance over generalized κ − μ and η − μ fading channels. In Nallagonda et al, 21 the energy‐efficiency performance is studied with CED‐CSS network over erroneous generalized κ − μ fading channels.…”

Section: Introductionmentioning

confidence: 99%

Analysis of energy‐efficient cooperative spectrum sensing with improved energy detectors and multiple antennas over Nakagami‐q/n fading channels

Nallagonda¹,

Mamidi

Bhowmick

2021

Int J Communication

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Summary Cognitive radio (CR) is an advanced technique used for the utilization of radio spectrum. A CR node uses the radio spectrum of a licensed user (called as primary user, PU) deviously. In this work, a cooperative sensing network (CSN) with improved energy detection (IED)‐based CR nodes is proposed. Each CR node consists of multiple antennas and perform themselves selection diversity (SC) technique. Each CR node senses a PU through erroneous sensing channel and reports its sensing data (1‐bit binary‐decision) to the fusion center (FC) through erroneous reporting channels. At FC, existence of PU (presence or absence) is identified using k‐out‐of‐N fusion rule. The novel expressions for detection probability over noise plus Nakagami‐q/n fading channels are derived and the mathematical frameworks for analysis of throughput and energy‐efficiency of the proposed network are developed. The simulation testbed is also developed and presented in this work to validate the analytically obtained performance characteristics. For several network parameters values, the investigation on comparison between IED and traditional energy detection method for various decision fusion rules is studied. Further, performance characteristics are analytically illustrated for throughput and energy‐efficiency over noise plus Nakagami‐q/n fading channels. The impact of diversity technique and effect of fading severity parameters on the throughput and energy‐efficiency are also investigated. The effect of channel error on total error performance for both proposed and conventional networks is shown. Finally, optimal fusion rule and optimal network parameters values correspond to maximum throughput and maximum energy‐efficiency are also identified.

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Throughput analysis of cooperative cognitive radio network over generalized κ–μ and η–μ fading channels

Cited by 15 publications

References 31 publications

Comprehensive performance analysis of data‐fusion aided cooperative cognitive radio network over η − μ fading channel

Comprehensive performance analysis of data‐fusion aided cooperative cognitive radio network over η − μ fading channel

Data fusion‐aided cognitive radio network over generalised fading channels

Analysis of energy‐efficient cooperative spectrum sensing with improved energy detectors and multiple antennas over Nakagami‐q/n fading channels

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