Proposed Technologies for Solving Future 5G Heterogeneous Networks Challenges

The evolution towards 5G mobile communication networks will be characterized by increasing number of wireless devices and service complexity, while the requirement to access mobile services will be essential. This paper presents an overview of the evolution of wireless networks, and focus on future mobile communication generation (5G) with its requirements, Challenges and Services. In addition, we propose a HetNet based architecture for 5G networks. The key ideas for each of the technologies are stated, along with the potential impact on 5G networks architecture.The proposed HetNet architecture key elements such as Small cells, Massive MIMO, mm-waves,  D2D communication, full-duplex communication, energy harvesting, Cloud-RAN and Wireless Network Virtualization,  all of these technologies serve together to ensure users with Quality of service (QoS) requirement in a spectrum & energy efficient manner. Keywords: 5G networks, wireless cellular networks, 5G networks, 5G heterogeneous network architecture, small cells, D2D communications, Massive MIMO, mm-wave, C-RAN, energy harvesting

System architecture and deployment scenarios for SESAME: small cEllS coordinAtion for Multi-tenancy and Edge services

The surge of the Internet traffic with exabytes of data flowing over operators’ mobile networks has created the need to rethink the paradigms behind the design of the mobile network architecture. The inadequacy of the 4G UMTS Long term Evolution (LTE) and even of its advanced version LTE-A is evident, considering that the traffic will be extremely heterogeneous in the near future and ranging from 4K resolution TV to machine-type communications. To keep up with these changes, academia, industries and EU institutions have now engaged in the quest for new 5G technology. In this paper we present the innovative system design, concepts and visions developed by the 5G PPP H2020 project SESAME (Small cEllS coordinAtion for Multi-tenancy and Edge services). The innovation of SESAME is manifold: i) combine the key 5G small cells with cloud technology, ii) promote and develop the concept of Small Cells-as-a-Service (SCaaS), iii) bring computing and storage power at the mobile network edge through the development of non-x86 ARM technology enabled micro-servers, and iv) address a large number of scenarios and use cases applying mobile edge computing

A cloud-enabled small cell architecture in 5G networks for broadcast/multicast services

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The evolution of 5G suggests that communication networks become sufficiently flexible to handle a wide variety of network services from various domains. The virtualization of small cells as envisaged by 5G, allows enhanced mobile edge computing capabilities, thus enabling network service deployment and management near the end user. This paper presents a cloud-enabled small cell architecture for 5G networks developed within the 5G-ESSENCE project. This paper also presents the conformity of the proposed architecture to the evolving 5G radio resource management architecture. Furthermore, it examines the inclusion of an edge enabler to support a variety of virtual network functions in 5G networks. Next, the improvement of specific key performance indicators in a public safety use case is evaluated. Finally, the performance of a 5G enabled evolved multimedia broadcast multicast services service is evaluated.Peer ReviewedPostprint (author's final draft

Energy Efficiency Analysis of Heterogeneous Cache-enabled 5G Hyper Cellular Networks

The emerging 5G wireless networks will pose extreme requirements such as high throughput and low latency. Caching as a promising technology can effectively decrease latency and provide customized services based on group users behaviour (GUB). In this paper, we carry out the energy efficiency analysis in the cache-enabled hyper cellular networks (HCNs), where the macro cells and small cells (SCs) are deployed heterogeneously with the control and user plane (C/U) split. Benefiting from the assistance of macro cells, a novel access scheme is proposed according to both user interest and fairness of service, where the SCs can turn into semi- sleep mode. Expressions of coverage probability, throughput and energy efficiency (EE) are derived analytically as the functions of key parameters, including the cache ability, search radius and backhaul limitation. Numerical results show that the proposed scheme in HCNs can increase the network coverage probability by more than 200% compared with the single- tier networks. The network EE can be improved by 54% than the nearest access scheme, with larger research radius and higher SC cache capacity under lower traffic load. Our performance study provides insights into the efficient use of cache in the 5G software defined networking (SDN)

Control and data channel resource allocation in OFDMA heterogeneous networks

This paper investigates the downlink resource allocation problem in Orthogonal Frequency Division Multiple Access (OFDMA) Heterogeneous Networks (HetNets) consisting of macro cells and small cells sharing the same frequency band. Dense deployment of small cells overlaid by a macro layer is considered to be one of the most promising solutions for providing hotspot coverage in future 5G networks. The focus is to devise an optimised policy for small cells’ access to the shared spectrum, in terms of their transmissions, in order to keep small cell served users sum data rate at high levels while ensuring that certain level of quality of service (QoS) for the macro cell users in the vicinity of small cells is provided. Both data and control channel constraints are considered, to ensure that not only the macro cell users’ data rate demands are met, but also a certain level of Bit Error Rate (BER) is ensured for the control channel information. Control channel reliability is especially important as it holds key information to successfully decode the data channel. The problem is addressed by our proposed linear binary integer programming heuristic algorithm which maximises the small cells utility while ensuring the macro users imposed constraints. To further reduce the computational complexity, we propose a progressive interference aware low complexity heuristic solution. Discussion is also presented for the implementation possibility of our proposed algorithms in a practical network. The performance of both the proposed algorithms is compared with the conventional Reuse-1 scheme under different fading conditions and small cell loads. Results show a negligible drop in small cell performance for our proposed schemes, as a trade-off for ensuring all macro users data rate demands, while Reuse-1 scheme can even lead up to 40 % outage when control region of the small cells in heavily loaded

Automatic backhaul planning for 5G Open RAN Networks based on MNO Data

The Quality of Service (QoS) requirements for the 5th Generation (5G) services are ambitious and broad, particularly for the latency targets. To cover those, a flexible and cost-efficient Radio Access Network (RAN) is essential as proposed by the Open-RAN (O-RAN) concept. In addition, the deployment of O-RAN 5G networks can be expedited by considering network access, aggregation, and core locations of legacy technologies, where physical requisites as power supply, fiber optic links, and others are already met. With this in mind, this paper extends previous simulation work that proposed a radio network planning algorithm for 5G Millimeter Wave (mmWave) small cells to O-RAN-based networks. The backhaul planning algorithm considers both the 5G/O-RAN QoS constraints, a real 4th Generation (4G) network topology, and the respective Key Performance Indicators (KPIs) from a Mobile Network Operator (MNO) as the foundation to plan an O-RAN compliant backhaul network. Our findings identified that the latency of current networks is greatly determined by the network load. In the utmost case, comparing the network baseline and busy hour KPIs, the baseline planned O-RAN network requires 7%of the equivalent busy hour network nodes. This approach has the potential to help MNOs to outline an enlightened strategy, minimizing Capital Expenditure (CAPEX) and augmenting QoS towards upgrading legacy networks to O-RAN 5G networks.info:eu-repo/semantics/publishedVersio

D2D-based Cooperative Positioning Paradigm for Future Wireless Systems: A Survey

Emerging communication network applications require a location accuracy of less than 1m in more than 95% of the service area. For this purpose, 5G New Radio (NR) technology is designed to facilitate high-accuracy continuous localization. In 5G systems, the existence of high-density small cells and the possibility of the device-to-device (D2D) communication between mobile terminals paves the way for cooperative positioning applications. From the standardization perspective, D2D technology is already under consideration (5G NR Release 16) for ultra-dense networks enabling cooperative positioning and is expected to achieve the ubiquitous positioning of below one-meter accuracy, thereby fulfilling the 5G requirements. In this survey, the strengths and weaknesses of D2D as an enabling technology for cooperative cellular positioning are analyzed (including two D2D approaches to perform cooperative positioning); lessons learned and open issues are highlighted to serve as guidelines for future research

Cloud-based implementation of a SON radio resources planning system for mobile networks and integration in SaaS metric

In mobile network deployments of growing size, the optimum and fast planning of radio resources are a key task. Cloud services enable efficient and scalable implementation of procedures and algorithms. In this paper, a proof of concept implementation of a cloud-based network planning work pattern using Amazon Web Services (AWS) is presented, containing new and efficient radio resource planning algorithms for 3G, 4G and 5G systems. It extracts configuration and performance data from the network, enabling to accurately estimate cells coverage, identify neighboring cells and optimally plan scrambling codes (SCs) and physical cell identity (PCI) in 3G and 4G/5G networks, respectively. This implementation was integrated and is available in the commercial Metric Software-as-a-Service (SaaS) monitoring and planning tool. The cloud-based planning system is demonstrated in various canonical and realistic Universal Mobile Telecommunications System (UMTS) and Long Term Evolution (LTE) scenarios, and compared to an algorithm previously used by Metric. For a small LTE realistic scenario consisting of 9 sites and 23 cells, it takes less than 0.6 seconds to perform the planning. For an UMTS realistic scenario with 12 484 unplanned cells, the planning is efficiently achieved, taking less than 8 seconds, and guaranteeing no collisions between first order neighboring cells. The proposed concept is proved, as this system, capable of automatically planning 3/4/5G realistic networks of multi-vendor equipment, makes Metric more attractive to the market.info:eu-repo/semantics/publishedVersio

Resource Allocation Energy Efficient Algorithm for H-CRAN in 5G

In today's generation, the demand for data rates has also increased due to the rapid surge in the number of users. With this increasing growth, there is a need to develop the next fifth generation network keeping in mind the need to replace the current 4G cellular network. The fifth generation (5G) design in mobile communication technology has been developed keeping in mind all the communication needs of the users. Heterogeneous Cloud Radio Access Network (H-CRAN) has emerged as a capable architecture for the newly emerging network infrastructure for energy efficient networks and high data rate enablement. It is considered as the main technology. Better service quality has been achieved by developing small cells into macro cells through this type of network. In addition, the reuse of radio resources is much better than that of homogeneous networks. In the present paper, we propose the H-CRAN energy-efficient methods. This energy-efficient algorithm incorporates an energy efficient resource allocation management design to deal to heterogeneous cloud radio access networks in 5G. System throughput fulfillment is elevating by incorporating an efficient resource allocation design by the energy consumption model. The simulation results have been demonstrated by comparing the efficiency of the introduced design with the existing related design