Currently, modern devices and applications for communications need huge frequency bands since it has limited resources. To address this issue, the cognitive radio is considered a promised solution where its main function is exploiting the idle spectrum using one of spectrum sensing (SS) techniques. A energy detection (ED) for SS technique that handles low signal-to-noise ratio (SNR) signals is proposed in this paper. It is derived using the discrete cosine transform (DCT) according to Welch's periodogram to estimate the power spectral density (PSD). The proposed technique is applied to sense the digital video broadcast (DVB) via AWGN channel with various SNR values and various user terminals. The results of the proposed technique proved that its performance is better than the conventional Welch's algorithm for both cases of low SNR and multi user terminals.
There are many problems in cellular communications cannot be resolved traditionally. The quantum communications can add new dimensions, safety, encryption and solution to the traditional networks because of its robust physical strength. However, it is not entirely realised how to adapt the quantum into the traditional communications because it is not entirely utilised. This paper addresses the necessary guidelines and assessments for future quantum solutions to the standard mobile cloud networks. In particular, using entanglement phenomenon to increase the performance of the X2 application (X2-AP) protocol by minimising the overhead signalling, represented by the time and energy consumption the conventional cloud encounters. We intended to offer a delay reduction while adapting the quantum technique into the cloud by modelling the latency of both paradigms. Finally, increasing the number of photons has decreased the delay to about 40% compared to the traditional network. In addition, the energy efficiency in the quantum case has been increased while decreasing the power consumption by about 10%.
<p><span>In cloud mobile networks, precise assessment for the position of the virtualization powered cloud center would improve the capacity limit, latency and energy efficiency (EEf). This paper utilized the Monte Carlo oriented particle swarm optimization (PSO) and genetic algorithm (GA) to first, obtain the optimal number of virtual machines (VMs) that maximize the EEf of the mobile cloud center, second, optimize the position of the mobile data center. To fulfil such examination, a power evaluation framework is proposed to shape the power utilization of a virtualized server while hosting an amount of VMs. In addition, the total power consumption of the network is examined, including data center and radio units (RUs). This evaluation is based on linear modelling of the network parameters, such as resource blocks, number of VMs, transmitted and received powers, and overhead power consumption. Finally, the EEf is constrained to many quality of service (QoS) metrics, including number of resource blocks, total latency and minimum user's data rate.</span></p>
Towards offering productive organizations and clean condition, green organization is an essential for the future correspondence ages. This paper talks about the comprehensive and best compromises that are simultaneous with empowering the green advancement. This paper numerically assesses the impacts of the numerous measurements and factors, for example, powering sufficiency, deployment cost, revenue, economy dimension, delay up on CO2 emission, bandwidth, consumed power, cost efficiency, transmitted power, energy efficiency and spectral efficiency. This work likewise shows that green situated organizations may think about generally significant expense productivity. In like manner, the organization suppliers and financial specialists can decide after utilizing the suitable wellspring of vitality and supporters one of them.
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