Efficient energy management in ultra-dense wireless networks

The increase in demand for more network capacity has led to the evolution of wireless networks from being largely Heterogeneous (Het-Nets) to the now existing Ultra-dense (UDNs). In UDNs, small cells are densely deployed with the goal of shortening the physical distance between the base stations (BSs) and the UEs, so as to support more user equipment (UEs) at peak times while ensuring high data rates. Compared to Het-Nets, Ultra-dense networks (UDNs) have many advantages. These include, more network capacity, higher flexibility to routine configurations, and more suitability to achieve load-balancing, hence, fewer blind spots as well as lower call blocking probability. It should be noted that, in practice, due to the high density of deployed small cells in Ultra-Dense Networks, a number of issues, or rather concerns, come with this evolution from Het-Nets. Among these issues include problems with efficient radio resource management, user cell association, inter- and intra-cell interference management and, last but not least, efficient energy consumption. Some of these issues which impact the overall network efficiency are largely due to the use of obsolete algorithms, especially those whose resource allocation is based solely on received signal power (RSSP). In this paper, the focus is solely on the efficient energy management dilemma and how to optimally reduce the overall network energy consumption. Through an extensive literature review, a detailed report into the growing concern of efficient energy management in UDNs is provided in Chapter 2. The literature review report highlights the classification as well as the evolution of some of the Mobile Wireless Technologies and Mobile Wireless Networks in general. The literature review report provides reasons as to why the energy consumption issue has become a very serious concern in UltraDense networks as well as the various techniques and measures taken to mitigate this. It is shown that, due to the increasing Mobile Wireless Systems’ carbon footprint which carries serious negative environmental impact, and the general need to lower operating costs by the network operators, the management of energy consumption increases in priority. By using the architecture of a Fourth Generation Long Term Evolution (4G-LTE) UltraDense Network, the report further shows that more than 65% of the overall energy consumption is by the access network and base stations in particular. This phenomenon explains why most attention in energy efficiency management in UDNs is largely centred on reducing the energy consumption of the deployed base stations more than any other network components like the data servers or backhauling features used. Furthermore, the report also provides detailed information on the methods/techniques, their classification, implementation, as well as a critical analysis of the said implementations in literature. This study proposes a sub-optimal algorithm and Distributed Cell Resource Allocation with a Base Station On/Off scheme that aims at reducing the overall base station power consumption in UDNs, while ensuring that the overall Quality of Service (QoS) for each User Equipment (UE) as specified in its service class is met. The modeling of the system model used and hence formulation of the Network Energy Efficiency (NEE) optimization problem is done viii using stochastic geometry. The network model comprises both evolved Node B (eNB) type macro and small cells operating on different frequency bands as well as taking into account factors that impact NEE such as UE mobility, UE spatial distribution and small cells spatial distribution. The channel model takes into account signal interference from all base stations, path loss, fading, log normal shadowing, modulation and coding schemes used on each UE’s communication channels when computing throughout. The power consumption model used takes into account both static (site cooling, circuit power) and active (transmission or load based) base station power consumption. The formulation of the NEE optimization problem takes into consideration the user’s Quality-of-service (QoS), inter-cell interference, as well as each user’s spectral efficiency and coverage/success probability. The formulated NEE optimization problem is of type Nondeterministic Polynomial time (NP)-hard, due to the user-cell association. The proposed solution to the formulated optimization problem makes use of constraint relaxation to transform the NP-hard problem into a more solvable, convex and linear optimization one. This, combined with Lagrangian dual decomposition, is used to create a distributed solution. After cellassociation and resource allocation phases, the proposed solution in order to further reduce power consumption performs Cell On/Off. Then, by using the computer simulation tools/environments, the “Distributed Resource Allocation with Cell On/Off” scheme’s performance, in comparison to four other resource allocation schemes, is analysed and evaluated given a number of different network scenarios. Finally, the statistical and mathematical results generated through the simulations indicate that the proposed scheme is the closest in NEE performance to the Exhaustive Search algorithm, and hence superior to the other sub-optimal algorithms it is compared to

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

Project Final Report – FREEDOM ICT-248891

This document is the final publishable summary report of the objective and work carried out within the European Project FREEDOM, ICT-248891.This document is the final publishable summary report of the objective and work carried out within the European Project FREEDOM, ICT-248891.Preprin

The electronically steerable parasitic array radiator antenna for wireless communications : signal processing and emerging techniques

Smart antenna technology is expected to play an important role in future wireless communication networks in order to use the spectrum efficiently, improve the quality of service, reduce the costs of establishing new wireless paradigms and reduce the energy consumption in wireless networks. Generally, smart antennas exploit multiple widely spaced active elements, which are connected to separate radio frequency (RF) chains. Therefore, they are only applicable to base stations (BSs) and access points, by contrast with modern compact wireless terminals with constraints on size, power and complexity. This dissertation considers an alternative smart antenna system the electronically steerable parasitic array radiator (ESPAR) which uses only a single RF chain, coupled with multiple parasitic elements. The ESPAR antenna is of significant interest because of its flexibility in beamforming by tuning a number of easy-to-implement reactance loads connected to parasitic elements; however, parasitic elements require no expensive RF circuits. This work concentrates on the study of the ESPAR antenna for compact transceivers in order to achieve some emerging techniques in wireless communications. The work begins by presenting the work principle and modeling of the ESPAR antenna and describes the reactance-domain signal processing that is suited to the single active antenna array, which are fundamental factors throughout this thesis. The major contribution in this chapter is the adaptive beamforming method based on the ESPAR antenna. In order to achieve fast convergent beamforming for the ESPAR antenna, a modified minimum variance distortionless response (MVDR) beamfomer is proposed. With reactance-domain signal processing, the ESPAR array obtains a correlation matrix of receive signals as the input to the MVDR optimization problem. To design a set of feasible reactance loads for a desired beampattern, the MVDR optimization problem is reformulated as a convex optimization problem constraining an optimized weight vector close to a feasible solution. Finally, the necessary reactance loads are optimized by iterating the convex problem and a simple projector. In addition, the generic algorithm-based beamforming method has also studied for the ESPAR antenna. Blind interference alignment (BIA) is a promising technique for providing an optimal degree of freedom in a multi-user, multiple-inputsingle-output broadcast channel, without the requirements of channel state information at the transmitters. Its key is antenna mode switching at the receive antenna. The ESPAR antenna is able to provide a practical solution to beampattern switching (one kind of antenna mode switching) for the implementation of BIA. In this chapter, three beamforming methods are proposed for providing the required number of beampatterns that are exploited across one super symbol for creating the channel fluctuation patterns seen by receivers. These manually created channel fluctuation patterns are jointly combined with the designed spacetime precoding in order to align the inter-user interference. Furthermore, the directional beampatterns designed in the ESPAR antenna are demonstrated to improve the performance of BIA by alleviating the noise amplification. The ESPAR antenna is studied as the solution to interference mitigation in small cell networks. Specifically, ESPARs analog beamforming presented in the previous chapter is exploited to suppress inter-cell interference for the system scenario, scheduling only one user to be served by each small BS at a single time. In addition, the ESPAR-based BIA is employed to mitigate both inter-cell and intracell interference for the system scenario, scheduling a small number of users to be simultaneously served by each small BS for a single time. In the cognitive radio (CR) paradigm, the ESPAR antenna is employed for spatial spectrum sensing in order to utilize the new angle dimension in the spectrum space besides the conventional frequency, time and space dimensions. The twostage spatial spectrum sensing method is proposed based on the ESPAR antenna being targeted at identifying white spectrum space, including the new angle dimension. At the first stage, the occupancy of a specific frequency band is detected by conventional spectrum-sensing methods, including energy detector and eigenvalue-based methods implemented with the switched-beam ESPAR antenna. With the presence of primary users, their directions are estimated at the second stage, by high-resolution angle-of-arrival (AoA) estimation algorithms. Specifically, the compressive sensing technology has been studied for AoA detection with the ESPAR antenna, which is demonstrated to provide high-resolution estimation results and even to outperform the reactance-domain multiple signal classification

Millimeter Wave Cellular Networks: A MAC Layer Perspective

The millimeter wave (mmWave) frequency band is seen as a key enabler of multi-gigabit wireless access in future cellular networks. In order to overcome the propagation challenges, mmWave systems use a large number of antenna elements both at the base station and at the user equipment, which lead to high directivity gains, fully-directional communications, and possible noise-limited operations. The fundamental differences between mmWave networks and traditional ones challenge the classical design constraints, objectives, and available degrees of freedom. This paper addresses the implications that highly directional communication has on the design of an efficient medium access control (MAC) layer. The paper discusses key MAC layer issues, such as synchronization, random access, handover, channelization, interference management, scheduling, and association. The paper provides an integrated view on MAC layer issues for cellular networks, identifies new challenges and tradeoffs, and provides novel insights and solution approaches.Comment: 21 pages, 9 figures, 2 tables, to appear in IEEE Transactions on Communication

LTE-Advanced radio access enhancements: A survey

Long Term Evolution Advanced (LTE-Advanced) is the next step in LTE evolution and allows operators to improve network performance and service capabilities through smooth deployment of new techniques and technologies. LTE-Advanced uses some new features on top of the existing LTE standards to provide better user experience and higher throughputs. Some of the most significant features introduced in LTE-Advanced are carrier aggregation, enhancements in heterogeneous networks, coordinated multipoint transmission and reception, enhanced multiple input multiple output usage and deployment of relay nodes in the radio network. Mentioned features are mainly aimed to enhance the radio access part of the cellular networks. This survey article presents an overview of the key radio access features and functionalities of the LTE-Advanced radio access network, supported by the simulation results. We also provide a detailed review of the literature together with a very rich list of the references for each of the features. An LTE-Advanced roadmap and the latest updates and trends in LTE markets are also presented