Radio resource management for hyper-dense heterogeneous small cell network in 5g and beyond

Laburpena

Future of communication with wireless network is about to see enormous growth, not only in number of users but also in different kind of services. Requirement of high quality of service is another critical aspect of demanding wireless communications and the explosion in number of users makes these requirements even more challenging. Hyper-dense heterogenous small cells are an integral part of 5G environment, and they suffer from high interference and imbalanced distribution of users. Therefore, identifying weak users and enabling them to achieve acceptable QoS is a crucial issue and important challenge to tackle. Radio resource and its management is a key area of innovation and research where technologies, infrastructure and challenges are rapidly changing as 5G system architecture demands a paradigm shift. The previous generation communication technologies require customizations and upgrades as 5G will remain inclusive for significantly long du- ration. Radio resource management schemes that are evolved during LTE/LTE-A network environment period will remain relevant for 5G, however, these schemes must become more intelligent and adaptive for future as features and requirements of network and users will be diverse and highly demanding [1]. Resource management in the era of 5G will pose more diverse challenges than previous generations, as physical requirements of 5G in terms of infrastructure is only one part of the problem. Moreover, inclusive nature of 5G architecture will require much more intelligent and robust techniques to solve the complex RRM problem. The support of legacy system and infrastructure will be needed for significant amount of time before 5G will reach everywhere with its true potential and defined features. Meeting the standard requirement of 5G in terms of data rate, traffic volume, latency, etc., is challenging enough, but continuing the support with previous generation (i.e., LTE/LTE-A, 3G) while moving forward, make the it even more difficult [2]. Also RRM in 5G is more challenging than the previous generations due to its architecture and standard requirements. Intelligent and robust RRM technique is essential to handle the issues of resource management. RRM is a complex and challenging problem because it requires solution of multiple issues such as interference management, spectrum utilization, fairness, QoS requirement, etc. An efficient RRM approach must consider various issues simultaneously without compromising the other key aspect of network requirement [3]. As fifth-generation networks are becoming a reality, and radio access network architectures are being redefined and rebuilt to accommodate the emerging specifications and demands. The future radio access networks need to incorporate in their architectural design smooth re-configurability and high flexibility without compromising the throughput and the perceived quality of the new services and traffic types that future networks introduce. Such densely distributed access networks suffer the effect of inter-cell interference. Robust and intelligent coordination of multiple access networks is required in order to minimize the effect of interference and maximize users gains. Coordinated among various operation is already considered as a promising technique for satisfying the challenges of the spectrum and interference management, especially for users at the edge of the cell coverage area. To increase the benefits of multiple cooperating technologies are used for optimizing service quality in dense small cell networks [4]. In todays wireless communication systems, the exponentially growing needs of mobile users require the combination of new and existing techniques to meet the demands for reliable and high-quality service provision. This may not always be possible, as the resources in wireless telecommunication systems are limited and a significant number of users, usually located at the cell edges, can suffer from se- vere interference. In this dissertation work, various technologies namely as joint transmission coordinated multi point, non-orthogonal multiple access, multi-user multiple input multiple output [5] and zero forcing beamforming are used along with a cooperative coalition formation game [3] for improving the weak users signal condition. A static user scenario is developed in simulation environment, and a cooperative coalition game scenario with JT-CoMP is compared with other scenarios, also findings are evaluated and analyzed for the while keeping the environment realistic. A hyper dense heterogeneous small cell environment is considered as the overall general architecture for the works in this dissertation. This is closely related to the scenario architecture of the H2020-MSCA-ITN-SECRET [6]. SECRET is SEcure network Coding for Reduced Energy next generation mobile small cells and a collaborative European Training Network (ETN) Consortium under the umbrella of Horizon 2020 projects. Hyperdense heterogeneous small cells are one of a principle enabler for 5G deployment in dense mobile environments. In such environments, where resources are scarce and efficient communications depend on a multitude of different parameters, CoMP communication is expected to bring visible gains in terms of energy savings, as well as capacity and coverage improvements. Toward this end, a hybrid mode of self-organized heterogeneous networks (HetNets) that exploits the benefits of both the centralized and distributed interference management approaches is proposed. Specifically, in a centralized architecture all management and control functions and algorithms are part of central controller where, operation and management tasks are executed. Centralization of the management operations requires timely and periodic feedback from every part of the network. These algorithms execution need feedback from the network, hence creating unwanted signaling overhead and increased complexity. On the other hand, the distributed management of interference requires each small cell to be capable of performing the required optimization algorithms. In such cases, small cells exchange information with each other utilizing the interfaces, while the exchanges between small cell BSs are completed with network listening. Although, the distributed optimization suffers from a lower performance rate due to the lack of global network optimality [7]. Game-theory-based cooperation between small cell sites is proposed to improve end-user experience for user devices served by coordinated BSs using joint processing.