Energy Efficiency in Hybrid Mobile and Wireless Networks

Wireless Internet access is almost pervasive nowadays, and many types of wireless networks can be used to access the Internet. However, along with this growth, there is an even greater concern about the energy consumption and efficiency of mobile devices as well as of the supporting networks, triggering the appearance of the concept of green communication. While some efforts have been made towards this direction, challenges still exist and need to be tackled from diverse perspectives. Cellular networks, WLANs, and ad hoc networks in the form of wireless mesh networks are the most popular technologies for wireless Internet access. The availability of such a variety of access networks has also paved the way to explore synergistic approaches for Internet access, leading to the concept of hybrid networks and relay communications. In addition, many mobile devices are being equipped with multiple interfaces, enabling them to operate in hybrid networks. In contrast, the improvements in the battery technology itself have not matched the pace of the emerging mobile applications. The situation becomes more sophisticated when a mobile device functions also as a relay node to forward other station’s data. In the literature, energy efficiency of mobile devices has been addressed from various perspectives such as protocol-level efforts, battery management efforts, etc. However, there is little work on energy efficiency in hybrid mobile and wireless networks and devices with heterogeneous connections. For example, when there are multiple networks available to a mobile device, how to achieve optimum long-term energy consumption of such a device is an open question. Furthermore, in today’s cellular networks, micro-, pico-, and femto-cells are the most popular network topologies in order to support high data rate services and high user density. With the growth of such small-cell solutions, the energy consumption of these networks is also becoming an important concern for operators. Towards this direction, various solutions have been proposed, ranging from deployment strategies for base stations to cooperative techniques etc. However, as base stations have the largest share in a network’s energy consumption, methods that allow lightly-loaded base stations sleep or be switched off are possible means as a feasible step towards green communications. In this dissertation, we tackle the above mentioned problems from two perspectives, i.e., mobile station’s and operator’s perspectives. More specifically, by taking into account the amount of transferred data in uplinks and downlinks individually for various components in a hybrid network, strategies are proposed to reduce mobile station’s battery energy consumption. For this purpose, other parameters such as link distance and remaining battery energy can also be considered for handover decision making, in order to maximize energy efficiency of the mobile station. To optimize long-term energy consumption of the mobile stations operated in such scenarios, a Markov decision process-based methodology is proposed as our contribution to this topic. Moreover, from operator’s perspective, a network energy conservation scheme which may switch off a base station is proposed for micro- or pico-cells scenarios. Both deterministic and probabilistic schemes are proposed for network energy conservation. The problems considered and the solutions proposed in this dissertation advance the frontiers of the research work within the theme of energy efficiency for mobile devices as well as hybrid mobile and wireless networks

A system-level power saving approach for cellular networks with microcells/picocells

Network power consumption reduction has recently become an active research topic. In this paper, we propose a novel approach to save power consumption of a three-cell microcellular network. When the traffic load in the middle cell is low, it can be switched-off and its users are covered. This is enabled by increasing the transmission power of one sector antenna in the two neighboring cells. Numerical results show that by increasing antenna transmission power of the two sectors, the overall network power consumption can be reduced

Capacity driven small cell deployment in heterogeneous cellular networks : Outage probability and rate coverage analysis

Author's accepted manuscript.This is the peer reviewed version of the following article: Ullah, A., Haq Abbas, Z., Muhammad, F., Abbas, G. & Lei, J. (2020). Capacity driven small cell deployment in heterogeneous cellular networks: Outage probability and rate coverage analysis. Transactions on Emerging Telecommunications Technologies, 31(6): e3876, which has been published in final form at https://doi.org/10.1002/ett.3876. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.acceptedVersio

Physical layer authentication using ensemble learning technique in wireless communications

Cyber-physical wireless systems have surfaced as an important data communication and networking research area. It is an emerging discipline that allows effective monitoring and efficient real-time communication between the cyber and physical worlds by embedding computer software and integrating communication and networking technologies. Due to their high reliability, sensitivity and connectivity, their security requirements are more comparable to the Internet as they are prone to various security threats such as eavesdropping, spoofing, botnets, man-in-the-middle attack, denial of service (DoS) and distributed denial of service (DDoS) and impersonation. Existing methods use physical layer authentication (PLA), the most promising solution to detect cyber-attacks. Still, the cyber-physical systems (CPS) have relatively large computational requirements and require more communication resources, thus making it impossible to achieve a low latency target. These methods perform well but only in stationary scenarios. We have extracted the relevant features from the channel matrices using discrete wavelet transformation to improve the computational time required for data processing by considering mobile scenarios. The features are fed to ensemble learning algorithms, such as AdaBoost, LogitBoost and Gentle Boost, to classify data. The authentication of the received signal is considered a binary classification problem. The transmitted data is labeled as legitimate information, and spoofing data is illegitimate information. Therefore, this paper proposes a threshold-free PLA approach that uses machine learning algorithms to protect critical data from spoofing attacks. It detects the malicious data packets in stationary scenarios and detects them with high accuracy when receivers are mobile. The proposed model achieves better performance than the existing approaches in terms of accuracy and computational time by decreasing the processing time

Analysis of load balancing and interference management in heterogeneous cellular networks

To meet the current cellular capacity demands, proactive offloading is required in heterogeneous cellular networks (HetCNets) comprising of different tiers of base stations (BSs), e.g., small-cell BSs (sBSs) and conventional macro-cell BSs (mBSs). Each tier differs from the others in terms of BS transmit power, spatial density, and association bias. Consequently, the coverage range of each tier BSs is also different from others. Due to low transmit power, a fewer number of users are associated to an sBS as compared with mBS. Thus, inefficient utilization of small-cell resources occurs. To balance the load across the network, it is necessary to push users to the underloaded small cells from the overloaded macro-cells. In co-channel deployed HetCNets, mBSs cause heavy inter-cell interference (ICI) to the offloaded users, which significantly affects the network performance gain. To address this issue, we develop a tractable analytical network model abating ICI using reverse frequency allocation (RFA) scheme along with cell range expansion-based user association. We probabilistically characterize coverage probability and user rate while considering RFA with and without selective sBS deployment. Our results demonstrate that selective sBS deployment outperforms other deployment methods.publishedVersionNivå

FedDP: A privacy-protecting theft detection scheme in smart grids using federated learning

In smart grids (SGs), the systematic utilization of consumer energy data while maintaining its privacy is of paramount importance. This research addresses this problem by energy theft detection while preserving the privacy of client data. In particular, this research identifies centralized models as more accurate in predicting energy theft in SGs but with no or significantly less data protection. Current research proposes a novel federated learning (FL) framework, namely FedDP, to tackle this issue. The proposed framework enables various clients to benefit from on-device prediction with very little communication overhead and to learn from the experience of other clients with the help of a central server (CS). Furthermore, for the accurate identification of energy theft, the use of a novel federated voting classifier (FVC) is proposed. FVC uses the majority voting-based consensus of traditional machine learning (ML) classifiers namely, random forests (RF), k-nearest neighbors (KNN), and bagging classifiers (BG). To the best of our knowledge, conventional ML classifiers have never been used in a federated manner for energy theft detection in SGs. Finally, substantial experiments are performed on the real-world energy consumption dataset. Results illustrate that the proposed model can accurately and efficiently detect energy theft in SGs while guaranteeing the security of client data

Two Teletraffic-based Schemes for Energy Saving in Cellular Networks with Micro-cells

Abstract — The energy consumption of Base Stations (BSs) is known to constitute a major part of the power consumption in a cellular network. In this paper, we propose a novel approach which may switch a BS off under light traffic conditions in order to conserve the power consumption of such networks. More specifically, when the traffic load in the middle cell of a network with three micro-cells is sufficiently low, the corresponding BS can be switched off and its users will be covered by increasing the transmission power of one sector antenna in each of the two neighboring cells. Two teletraffic-based power saving schemes are proposed in our study. The first scheme analyzes the expected sojourn times of different channel occupancies and switches off the BS deterministically when the switching thresholds are met. The second scheme instead switches off the BS probabilistically based on a policy designed using a Finite Markov Decision Process (FMDP). Numerical results for the first scheme demonstrate that a reasonable amount of network power can be saved at the cost of slightly higher transmission power. The results for the second scheme indicate that a lower limit on the long-term network transmission power can be obtained using the FMDP-based analysis. Index Terms — Micro-cell, teletraffic, power saving, energy, Markov chain, BS, FMDP, optimization

A continuous-space analytical approach for relay node placement in hybrid cellular and ad hoc networks

A hybrid network is composed of a cellular component and an ad hoc component connected by a relay node, for the purpose of coverage extension and/or capacity improvement. In this paper, we analyze the capacity of such a hybrid network by employing a continuous-space analytical methodology based on circular geometry for uniformly distributed nodes. To achieve maximal overall capacity, the relay node needs to be placed in an optimum location between the base station and the mobile station located at the boundary of the hybrid network. Numerical results show that for obtaining the optimum overall capacity for the hybrid network, the placement of the relay node should be in a range which is neither too close nor too far away from the base station. For a given node density and path-loss coefficient, a precise location for relay node placement to achieve maximum overall capacity can be found using the presented method

Power consumption analysis for mobile stations in hybrid relay-assisted wireless networks

Paper presented at the 2010 5th IEEE International Symposium on Wireless Pervasive Computing (ISWPC). (c) 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works. Paper also available from the publisher: http://dx.doi.org/10.1109/ISWPC.2010.5483733While Internet access using mobile or wireless technologies has become ubiquitous these days, the energy consumption aspect of such connections has not been studied in-depth yet. In this paper, a hybrid wireless network, which consists of a cellular component and a relay-assisted ad hoc component, is studied focusing on energy consumption by mobile stations with respect to the amount of data communicated and achieved battery lifetime. Four alternative paths are considered, including both pure cellular and hybrid ad hoc/cellular links for uplink and downlink traffic. The effects of each alternative connection on energy consumption of the involved mobile stations are analyzed in terms of the amount of data transferred and the operation time of the station's battery. The results from our analysis can also be used for proper relay selection in a hybrid link for achieving optimum data transfer from the Internet while keeping battery energy consumption of the mobile station and/or the relay station at a minimum level