A novel HGBBDSA-CTI approach for subcarrier allocation in heterogeneous network

In recent times, Heterogeneous Network (HetNet) achieves the capacity and coverage for indoors through the deployment of small cells i.e. femtocells (HeNodeBs). These HeNodeBs are plug-and-play Customer Premises Equipment’s which are associated with the internet protocol backhaul to macrocell (macro-eNodeB). The random placement of HeNodeBs deployed in co-channel along with macro-eNodeB is causing severe system performance degradation. Thereby, these HeNodeBs are suggested as the ultimate and the most significant cause of interference in Orthogonal Frequency-Division Multiple-Access based HetNets due to the restricted co-channel deployment. The CTI in such systems can significantly reduce the throughput, and the outages can rise to the unacceptable limit or extremely high levels. These lead to severe system performance degradation in HetNets. This paper presents a novel HGBBDSA-CTI approach capable of strategically allocate the subcarriers and thereby improves the throughput as well as the outage. The enhanced system performance is able to mitigate CTI issues in HetNets. This paper also analyses the time complexity for the proposed HGBBDSA algorithm and also compares it with the Genetic Algorithm-based Dynamic Subcarrier Allocation (DSA), and Particle Swarm Optimization-based DSA as well. The key target of this study is to allocate the unoccupied subcarriers by sharing among the HeNodeBs. The reason is also to enhance the system performance such as throughput of HeNodeB, the average throughput of HeNodeB Users, and outage. The simulation results show that the proposed HGBBDSA-CTI approach enhances the average throughput (92.05 and 74.44%), throughput (30.50 and 74.34%), and the outage rate reduced to 52.9 and 50.76% compare with the existing approaches. The result also indicates that the proposed HGBBDSA approach has less time complexity than the existing approaches

Energy-efficient cooperative resource allocation for OFDMA

Energy is increasingly becoming an exclusive commodity in next generation wireless communication systems, where even in legacy systems, the mobile operators operational expenditure is largely attributed to the energy bill. However, as the amount of mobile traffic is expected to double over the next decade as we enter the Next Generation communications era, the need to address energy efficient protocols will be a priority. Therefore, we will need to revisit the design of the mobile network in order to adopt a proactive stance towards reducing the energy consumption of the network. Future emerging communication paradigms will evolve towards Next Generation mobile networks, that will not only consider a new air interface for high broadband connectivity, but will also integrate legacy communications (LTE/LTE-A, IEEE 802.11x, among others) networks to provide a ubiquitous communication platform, and one that can host a multitude of rich services and applications. In this context, one can say that the radio access network will predominantly be OFDMA based, providing the impetus for further research studies on how this technology can be further optimized towards energy efficiency. In fact, advanced approaches towards both energy and spectral efficient design will still dominate the research agenda. Taking a step towards this direction, LTE/LTE-A (Long Term Evolution-Advanced) have already investigated cooperative paradigms such as SON (self-Organizing Networks), Network Sharing, and CoMP (Coordinated Multipoint) transmission. Although these technologies have provided promising results, some are still in their infancy and lack an interdisciplinary design approach limiting their potential gain. In this thesis, we aim to advance these future emerging paradigms from a resource allocation perspective on two accounts. In the first scenario, we address the challenge of load balancing (LB) in OFDMA networks, that is employed to redistribute the traffic load in the network to effectively use spectral resources throughout the day. We aim to reengineer the load-balancing (LB) approach through interdisciplinary design to develop an integrated energy efficient solution based on SON and network sharing, what we refer to as SO-LB (Self-Organizing Load balancing). Obtained simulation results show that by employing SO-LB algorithm in a shared network, it is possible to achieve up to 15-20% savings in energy consumption when compared to LTE-A non-shared networks. The second approach considers CoMP transmission, that is currently used to enhance cell coverage and capacity at cell edge. Legacy approaches mainly consider fundamental scheduling policies towards assigning users for CoMP transmission. We build on these scheduling approaches towards a cross-layer design that provide enhanced resource utilization, fairness, and energy saving whilst maintaining low complexity, in particular for broadband applications