5G Cellular: Key Enabling Technologies and Research Challenges

The evolving fifth generation (5G) cellular wireless networks are envisioned to provide higher data rates, enhanced end-user quality-of-experience (QoE), reduced end-to-end latency, and lower energy consumption. This article presents several emerging technologies, which will enable and define the 5G mobile communications standards. The major research problems, which these new technologies breed, as well as the measurement and test challenges for 5G systems are also highlighted.Comment: IEEE Instrumentation and Measurement Magazine, to appear in the June 2015 issue. arXiv admin note: text overlap with arXiv:1406.6470 by other author

A Framework for Enhancing the Energy Efficiency of IoT Devices in 5G Network

A wide range of services, such as improved mobile broadband, extensive machine-type communication, ultra-reliability, and low latency, are anticipated to be delivered via the 5G network. The 5G network has developed as a multi-layer network that uses numerous technological advancements to provide a wide array of wireless services to fulfil such a diversified set of requirements. Several technologies, including software-defined networking, network function virtualization, edge computing, cloud computing, and tiny cells, are being integrated into the 5G networks to meet the needs of various requirements. Due to the higher power consumption that will arise from such a complicated network design, energy efficiency becomes crucial. The network machine learning technique has attracted a lot of interest from the scientific community because it has the potential to play a crucial role in helping to achieve energy efficiency. Utilization factor, access latency, arrival rate, and other metrics are used to study the proposed scheme. It is determined that our system outperforms the present scheme after comparing the suggested scheme to these parameters

Spectrum- and Energy-Efficient Radio Resource Allocation for Wireless Communications

Wireless communications has been evolved significantly over the last decade. During this period, higher quality of service (QoS) requirements have been proposed to support various services. In addition, due to the increasing number of wireless devices and transmission, the energy consumption of the wireless networks becomes a burden. Therefore, the energy efficiency is considered as important as spectrum efficiency for future wireless communications networks, and spectrum and energy efficiency have become essential research topics in wireless communications. Moreover, due to the exploding of number mobile devices, the limited radio resources have become more and more scarce. With large numbers of users and various QoS requirements, a lot of wireless communications networks and techniques have emerged and how to effectively manage the limited radio resources become much more important. In this dissertation, we focus our research on spectrum- and energy-efficient resource allocation schemes in wireless communication networks. Recently, heterogeneous networks (HetNets) have been proposed and studied to improve the spectrum efficiency. In a two-tier heterogeneous network, small base stations reuse the same spectrum with macro base stations in order to support more transmission over the limited frequency bands. We design a cascaded precoding scheme considering both interference cancellation and power allocation for the two-tier heterogeneous network. Besides heterogeneous networks, as the fast development of intelligent transportation, we study the spectrum- and energy-efficient resource allocation in vehicular communication networks. The intelligent transportation and vehicular communications both have drawn much attention and are faced special wireless environment, which includes Doppler effects and severe uncertainties in channel estimation. A novel designed spectrum efficiency scheme is studied and verified. With consideration of energy efficiency, the device-to-device (D2D) enabled wireless network is an effective network structure to increase the usage of spectrum. From a device\u27s perspective, we design an energy-efficient resource allocation scheme in D2D communication networks. To improve the energy efficiency of wireless communication networks, energy harvesting technique is a powerful way. Recently, the simultaneous wireless information and power transfer (SWIPT) has been proposed as a promising energy harvesting method for wireless communication networks, based on which we derive an energy-efficient resource allocation scheme for SWIPT cooperative networks, which considers both the power and relay allocation. In addition to the schemes derivation for spectrum- and energy-efficient resource allocation, simulation results and the proofs of the proposed propositions are provided for the completeness of this dissertation

Wireless Powered Dense Cellular Networks: How Many Small Cells Do We Need?

This paper focuses on wireless powered 5G dense cellular networks, where base station (BS) delivers energy to user equipment (UE) via the microwave radiation in sub-6 GHz or millimeter wave (mmWave) frequency, and UE uses the harvested energy for uplink information transmission. By addressing the impacts of employing different number of antennas and bandwidths at lower and higher frequencies, we evaluate the amount of harvested energy and throughput in such networks. Based on the derived results, we obtain the required small cell density to achieve an expected level of harvested energy or throughput. Also, we obtain that when the ratio of the number of sub-6 GHz BSs to that of the mmWave BSs is lower than a given threshold, UE harvests more energy from a mmWave BS than a sub-6 GHz BS. We find how many mmWave small cells are needed to perform better than the sub-6 GHz small cells from the perspectives of harvested energy and throughput. Our results reveal that the amount of harvested energy from the mmWave tier can be comparable to the sub-6 GHz counterpart in the dense scenarios. For the same tier scale, mmWave tier can achieve higher throughput. Furthermore, the throughput gap between different mmWave frequencies increases with the mmWave BS density.Comment: pages 1-14, accepted by IEEE Journal on Selected Areas in Communication

Energy sustainable paradigms and methods for future mobile networks: A survey

In this survey, we discuss the role of energy in the design of future mobile networks and, in particular, we advocate and elaborate on the use of energy harvesting (EH) hardware as a means to decrease the environmental footprint of 5G technology. To take full advantage of the harvested (renewable) energy, while still meeting the quality of service required by dense 5G deployments, suitable management techniques are here reviewed, highlighting the open issues that are still to be solved to provide eco-friendly and cost-effective mobile architectures. Several solutions have recently been proposed to tackle capacity, coverage and efficiency problems, including: C-RAN, Software Defined Networking (SDN) and fog computing, among others. However, these are not explicitly tailored to increase the energy efficiency of networks featuring renewable energy sources, and have the following limitations: (i) their energy savings are in many cases still insufficient and (ii) they do not consider network elements possessing energy harvesting capabilities. In this paper, we systematically review existing energy sustainable paradigms and methods to address points (i) and (ii), discussing how these can be exploited to obtain highly efficient, energy self-sufficient and high capacity networks. Several open issues have emerged from our review, ranging from the need for accurate energy, transmission and consumption models, to the lack of accurate data traffic profiles, to the use of power transfer, energy cooperation and energy trading techniques. These challenges are here discussed along with some research directions to follow for achieving sustainable 5G systems.Comment: Accepted by Elsevier Computer Communications, 21 pages, 9 figure

Energy-efficient non-orthogonal multiple access for wireless communication system

Non-orthogonal multiple access (NOMA) has been recognized as a potential solution for enhancing the throughput of next-generation wireless communications. NOMA is a potential option for 5G networks due to its superiority in providing better spectrum efficiency (SE) compared to orthogonal multiple access (OMA). From the perspective of green communication, energy efficiency (EE) has become a new performance indicator. A systematic literature review is conducted to investigate the available energy efficient approach researchers have employed in NOMA. We identified 19 subcategories related to EE in NOMA out of 108 publications where 92 publications are from the IEEE website. To help the reader comprehend, a summary for each category is explained and elaborated in detail. From the literature review, it had been observed that NOMA can enhance the EE of wireless communication systems. At the end of this survey, future research particularly in machine learning algorithms such as reinforcement learning (RL) and deep reinforcement learning (DRL) for NOMA are also discussed

Stochastic Geometry Based Performance Study in 5G Wireless Networks

As the complexity of modern cellular networks continuously increases along with the evolution of technologies and the quick explosion of mobile data traffic, conventional large scale system level simulations and analytical tools become either too complicated or less tractable and accurate. Therefore, novel analytical models are actively pursued. In recent years, stochastic geometry models have been recognized as powerful tools to analyze the key performance metrics of cellular networks. In this dissertation, stochastic geometry based analytical models are developed to analyze the performance of some key technologies proposed for 5G mobile networks. Particularly, Device-to-Device (D2D) communication, Non-orthogonal multiple access (NOMA), and ultra-dense networks (UDNs) are investigated and analyzed by stochastic geometry models, more specifically, Poisson Point Process (PPP) models. D2D communication enables direct communication between mobile users in proximity to each other bypassing base station (BS). Embedding D2D communication into existing cellular networks brings many benefits such as improving spectrum efficiency, decreasing power energy consumption, and enabling novel location-based services. However, these benefits may not be fully exploited if the co-channel interference among D2D users and cellular users is not properly tackled. In this dissertation, various frequency reuse and power control schemes are proposed, aiming at mitigating the interference between D2D users and conventional cellular users. The performance gain of proposed schemes is analyzed on a system modeled by a 2-tier PPP and validated by numerical simulations. NOMA is a promising radio access technology for 5G cellular networks. Different with widely applied orthogonal multiple access (OMA) such as orthogonal frequency division multiple access (OFDMA) and single carrier frequency division multiple access (SC-FDMA), NOMA allows multiple users to use the same frequency/time resource and offers many advantages such as improving spectral efficiency, enhancing connectivity, providing higher cell-edge throughput, and reducing transmission latency. Although some initial performance analysis has been done on NOMA with single cell scenario, the system level performance of NOMA in a multi-cell scenario is not investigated in existing work. In this dissertation, analytical frameworks are developed to evaluate the performance of a wireless network with NOMA on both downlink and uplink. Distinguished from existing publications on NOMA, the framework developed in this dissertation is the first one that takes inter-cell interference into consideration. UDN is another key technology for 5G wireless networks to achieve high capacity and coverage. Due to the existence of line-of-sight (LoS)/non-line-of-sight (NLoS) propagation and bounded path loss behavior in UDN networks, the tractability of the original PPP model diminishes when analyzing the performance of UDNs. Therefore, a dominant BS (base station)-based approximation model is developed in this dissertation. By applying reasonable mathematical approximations, the tractability of the PPP model is preserved and the closed form solution can be derived. The numerical results demonstrate that the developed analytical model is accurate in a wide range of network densities. The analysis conducted in this dissertation demonstrates that stochastic geometry models can serve as powerful tools to analyze the performance of 5G technologies in a dense wireless network deployment. The frameworks developed in this dissertation provide general yet powerful analytical tools that can be readily extended to facilitate other research in wireless networks