Performance of Diversity System Output Signal in Mobile Cellular System in the Presence of α-μ Short Term Fading and Gamma Long Term Fading

Krstić, Dragana; Jakšić, Branimir; Gligorijević, Milan; Stefanović, Dušan; Stefanović, Mihajlo

doi:10.13164/re.2016.0757

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…A wireless mobile communication system with SC macrodiversity reception for the elimination of Gamma shadowing was analyzed in [53]. e macrodiversity system consists of three microdiversity SC receivers serving to mitigate α-μ short-term fading.…”

Section: Mitigation Of the Impact Of Fadingmentioning

confidence: 99%

Model-Driven Approach to Fading-Aware Wireless Network Planning Leveraging Multiobjective Optimization and Deep Learning

Krstić

Petrović

Al-Azzoni

2022

Mathematical Problems in Engineering

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Efficient resource planning is recognized as one of the key enablers making the large-scale deployment of next-generation wireless networks available for mass usage. Modelling, planning, and software simulation tools reduce both the time needed and costs of their tuning and realization. In this paper, we propose a model-driven framework for proactive network planning relying on synergy of deep learning and multiobjective optimization. The predictions about service demand and energy consumption are taken into account. Also, the impact of degradations resulting from fading and cochannel interference (CCI) effects is also considered. The optimization task is treated as a component allocation problem (CAP) aiming to find the best possible base station allocation for the considered smart city locations with respect to performance and service demand constraints. The goal is to maximize Quality of Service (QoS) while keeping the costs and energy consumption as low as possible. The adoption of a model-driven approach in combination with model-to-model transformations and automated code generation does not only reduce the complexity, making experimentation more rapid and convenient at the same time, but also increase the overall reusability and expandability of the planning tool. According to the obtained results, the proposed solution seems to be promising not only due to achieved benefits but also regarding the execution time, which is shorter than that achieved in our previous works, especially for larger distances. Further, we adopt model-based representation of handover strategies within the planning tool, enabling examination of the dynamic behavior of user-created plan, which is not exploited in other similar works. The main contributions of the paper are (1) wireless network planning (WNP) metamodel, a modelling notation for network plans; (2) model-to-model transformation for conversion of WNP to generalized CAP metamodel; (3) prediction problem (PP) metamodel, high-level abstraction for representation of prediction-related regression and classification problems; (4) code generator that creates PyTorch neural network from PP representation; (5) service demand and energy consumption prediction modules performing regression; (6) multiobjective optimization model for base station allocation; (7) Handover Strategy (HS) metamodel used for description of dynamic aspects and adaptability relevant to network planning.

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Section: Mitigation Of the Impact Of Fadingmentioning

confidence: 99%

Model-Driven Approach to Fading-Aware Wireless Network Planning Leveraging Multiobjective Optimization and Deep Learning

Krstić

Petrović

Al-Azzoni

2022

Mathematical Problems in Engineering

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“…Signals from antennas are combined in different ways. The combination techniques used to reduce the fading impact on the system performance are maximum-ratio combining (MRC), equal-gain combining (EGC), selection combining (SC) and switch-and-stay combining (SSC) [12,13].…”

Section: Introductionmentioning

confidence: 99%

Impacts of Diversity Technique Application in Order to Reduce the Fading in IEEE 802.15.4 Networks

Jaksic,

Todorovic,

Jovanovic

et al. 2023

Applied Sciences

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The paper discusses the operation of wireless sensor networks consisting of nodes based on the IEEE 802.15.4 ZigBee transceiver operating in the presence of Rayleigh or Nakagami-m fading, additive white Gaussian noise (AWGN) and interference. Analytical expressions for bit error rate (BER) for the IEEE 802.15.4 network were obtained when Rayleigh and Nakagami-m fading were processed with a selection-combining (SC) and maximum-ratio-combining (MRC) combiner and when AWGN and interference were present. Analytical results are presented graphically in the form of BER change, depending on the signal-to-noise ratio (SNR) for different values of network parameters: fading parameter (m), number of branches of MRC combiner (L), modulation parameter (M), and spreading sequence lengths (Lc). Graphical results are presented for the system when there are no combiners and when the SC and MRC combiners are included. Numerical results were confirmed by Monte Carlo simulation. Analysis of the SC and MRC combiner application impact on the performance improvement of the IEEE 802.15.4 network and the received signal was performed.

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Level crossing rate of macrodiversity system with three microdiversity receivers over shadowed weibull fading channel

Krstić

Stefanović

Suljović

et al. 2017

2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM)

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Performance of Diversity System Output Signal in Mobile Cellular System in the Presence of α-μ Short Term Fading and Gamma Long Term Fading

Cited by 3 publications

References 9 publications

Model-Driven Approach to Fading-Aware Wireless Network Planning Leveraging Multiobjective Optimization and Deep Learning

Model-Driven Approach to Fading-Aware Wireless Network Planning Leveraging Multiobjective Optimization and Deep Learning

Impacts of Diversity Technique Application in Order to Reduce the Fading in IEEE 802.15.4 Networks

Level crossing rate of macrodiversity system with three microdiversity receivers over shadowed weibull fading channel

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