Hybrid spectrum management using integrated fuzzy and femtocells in cognitive domain

In Today’s pandemic situation, ‘Spectrum accessing and smart usage’ is the sacred Mantra uttered by every individual citizen in the world. Work from home for techies, online classes for students, games for kids, webinar for teaching fraternity etc., are going almost on indoor coverage without any limit in pace because of the smart spectrum coverage by the network service providers. This paper provides an add-on facility to the existing wireless infrastructure to provide a better user experience in this highly regrettable routine. In this paper, a cognitive domain unused spectrum holes are efficiently handled by (i) adaptive spectrum management technique; (ii) Fuzzy Inference System based spectrum administration and (iii) Hybrid Cognitive Femtocell approaches based on the user demand and their applications. The proposed integrated cognitive femtocell and Fuzzy-based approach reduces the indoor coverage problems and enhances the throughput of the macrocell users by allowing adaptive spectrum management based on the demand, thereby eliminating spectrum underlay and overlay problems during critical conditions. In cognitive femtocell networks, the access points are prepared and installed with Cognitive Radio which can determine spectrum dynamically by macrocells and nearby Femto Access Points. It adjusts its radiating parameters to evade the macrocells’ interferences and the neighbouring femtocells, thereby maximising the spectrum band’s overall utility.

Power and Radio Resource Management in Femtocell Networks for Interference Mitigation

The growth of mobile traffic volume has been exploded because of the rapid improvement of mobile devices and their applications. Heterogeneous networks (HetNets) can be an attractive solution in order to adopt the exponential growth of wireless data. Femtocell networks are accommodated within the concept of HetNets. The implementation of femtocell networks has been considered as an innovative approach that can improve the network’s capacity. However, dense implementation and installation of femtocells would introduce interference, which reduces the network’s performance. Interference occurs when two adjacent femtocells are operated with the same radio resources. In this work, a scheme, which comprises two stages, is proposed. The first step is to distribute radio resources among femtocells, where each femtocell can identify the source of the interference. A constructed table is generated in order to measure the level of interference for each femtocell. Accordingly, the level of interference for each sub-channel can be recognized by all femtocells. The second stage includes a mechanism that helps femtocell base stations adjust their transmission power autonomously to alleviate the interference. It enforces a cost function, which should be realized by each femtocell. The cost function is calculated based on the production of undesirable interference impact, which is introduced by each femtocell. Hence, the transmission power is adjusted autonomously, where undesirable interference can be monitored and alleviated. The proposed scheme is evaluated through a MATLAB simulation and compared with other approaches. The simulation results show an improvement in the network’s capacity. Furthermore, the unfavorable impact of the interference can be managed and alleviated.

A trade-off between Energy Efficiency and Spectral Efficiency in macro-femtocell networks

<div>Obtaining large spectral efficiency (SE) and energy efficiency (EE) subject to quality of experience (QoE) is one of the prime concerns for the wireless next generation networks, however a major confrontation with its trade-off which is becoming apparent while optimizing both SE and EE parameters concurrently. In this work, an analytical framework for a cognitive-femtocell network is proposed to be dealt with and overcome the situations regarded as unwelcome. Here, the conflict of SE-EE trade-off in downlink (DL) transmission is expressed methodically by Pareto Optimal Set (POS) based on a multi-empirical most effective use of a resource scheme as a function of femto base station (FBS) and macro base station (MBS) transmit power and base station (BS) density, respectively. Then, SE and EE are formulated in a utility function by applying Cobb-Douglas production function to transform the multi- mpirical difficulty into the single-empirical optimization case. Besides, it is analytically shown that the SE-EE trade-off can be optimize through a distinctive universal optimum among the Pareto optimal by fine tuning the weighting metric other than BS transmit power and density, respectively. Simulation results validate that it is possible to obtain the EE-SE trade-off with SINR threshold at different weighting factor.</div>