Heterogeneous network optimization using robust power-and-resource based algorithm

In order to meet the increasing mobile data-traffic, spatial densification of network with several low-power nodes, the high-power macro BS and HetNet are the major key enabling solution. However, the HetNet is unplanned in nature, causes irregularities and interferences that without any user association rules. The appropriate deployment of the femto-cell in HetNet can provide effective traffic offloading, where the alleviate mobbing in the macro-cells can decrease the power consumption therefore it optimizes the user experience. Moreover, the protection is also important for the macro and femto cell users in a network through maintaining the min-max level of interferences. In this paper, we proposed RPRA that comprises two robust approach such as robust power-controller and the robust channel-allocation approach, which can improve the spectral efficiency and user experiences at lower network coverage areas via eliminating the week coverage zones. Also provide high user rate connection by effective interference in an efficient spectrum, lowering in transmission power and cost-effectiveness via less time delay. To show the effectiveness of our proposed model we have compared with several existing techniques and we got significant improvement in throughput, also reduction in time delay and transmission power

Channel Capacity Maximization using NQHN Approach at Heterogeneous Network

In present scenario, the high speed data transmission services has pushed limits for wireless communication network capacity, at same time multimedia transmission in real-time needs provision of QoS, therefore the network capacity and small cell coverage has comes with lots of challenges. Improving the channel capacity and coverage area within the available bandwidth is necessary to provide better QoS to users, and improved channel capacity for the FCUs and MCUs in network. In this paper, we are proposing an NQHN approach that incorporate with efficient power allocation, improving the channel capacity by optimized traffic scheduling process in a small cell HetNets scenario. This work efficiently handle the interference with maintaining the user QoS and the implemented power controller uses HeNB power as per the real time based approach for macro-cell and femto-cell. Moreover, we consider the real traffic scenario to check the performance of our proposed approach with respect to existing algorith

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe