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Human activity recognition (HAR) using wearable sensors enables continuous monitoring for healthcare applications. However, the conventional centralised training of deep learning models on sensor data poses challenges related to privacy, communication costs, and on-device efficiency. This paper proposes a federated learning framework integrating spiking neural networks (SNNs) with long short-term memory (LSTM) networks for energy-efficient and privacy-preserving HAR. The hybrid spiking-LSTM (S-LSTM) model synergistically combines the event-driven efficiency of SNNs and the sequence modelling capability of LSTMs. The model is trained using surrogate gradient learning and backpropagation through time, enabling fully supervised end-to-end learning. Extensive evaluations of two public datasets demonstrate that the proposed approach outperforms LSTM, CNN, and S-CNN models in accuracy and energy efficiency. For instance, the proposed S-LSTM achieved an accuracy of 97.36% and 89.69% for indoor and outdoor scenarios, respectively. Furthermore, the results also showed a significant improvement in energy efficiency of 32.30%, compared to simple LSTM. Additionally, we highlight the significance of personalisation in HAR, where fine-tuning with local data enhances model accuracy by up to 9% for individual users. [ABSTRACT FROM AUTHOR]

This paper aims the development of a new reduced-cost algorithm for a multi-objective robust transmitter placement under uncertainty. Toward this end, we propose a new hybrid Kriging/Grey Wolf Optimizer (GWO) approach combined with robust design optimization to estimate the set of Pareto frontier by searching robustness as well as accuracy (lower objective function) in a design space. We consider minimization of the energy power consumption for transmitting as well as maximization of signal coverage in a multi-objective robust optimization model. The reliability of the model to control signal overlap for multiple transmitting antennas is also provided. To smooth computational cost, the proposed method instead of evaluating all receiver test points in each optimization iteration approximates signal coverages using Kriging interpolation to obtain optimal transmitter positions. The results demonstrate the utility and the efficiency of the proposed method in rendering the robust optimal design and analyzing the sensitivity of the transmitter placement problem under practically less-expensive computational efforts (350% and 320% less than computational time elapsed using standalone GWO and NSGAII respectively). [ABSTRACT FROM AUTHOR]

The development of ultra-dense heterogeneous networks (HetNets) will cause a significant rise in energy consumption with large-scale base station (BS) deployments, requiring cellular networks to be more energy efficient to reduce operational expense and promote sustainability. Cell switching is an effective method to achieve the energy efficiency goals, but traditional heuristic cell switching algorithms are computationally demanding with limited generalization abilities for ultra-dense HetNet applications, motivating the usage of machine learning techniques for adaptive cell switching. Graph neural networks (GNNs) are powerful deep learning models with strong generalization abilities but receive little attention for cell switching. This paper proposes a GNN-based cell switching solution (GBCSS) that has a smaller computational complexity than existing heuristic algorithms. The presented performance evaluation uses the Milan telecommunication dataset based on real-world call detail records, comparing GBCSS with a traditional exhaustive search (ES) algorithm, a state-of-the-art learning-based algorithm, and the baseline without cell switching. Results indicate that GBCSS achieves a 10.41% energy efficiency gain when compared with the baseline and achieves 75.76% of the optimal performance obtained with ES algorithm. The results also demonstrate GBCSS' significant scalability and generalization abilities to differing load conditions and the number of BSs, suggesting this approach is well-suited to ultra-dense HetNet deployment. [ABSTRACT FROM AUTHOR]

Smart meters (SM) with wireless capabilities are one of the most meaningful applications of the Internet of Things. Standards like Zigbee have found a niche in transmitting data on energy usage to the user and the supplier wirelessly via these meters and communication hubs. There are still certain difficulties, notably in delivering wireless connectivity to meters situated in difficult-to-reach locations such as basements or deep indoors. To solve this issue, this paper investigates the usage of mesh networks at 868 MHz, particularly to increase coverage, and proposes an additional mounted antenna to significantly increase outside coverage while providing the necessary coverage extension for hard-to-reach indoor locations. Extensive measurements were made in Newbury in both suburban and open environments for validation and delivery of a simple statistical model for the 868 MHz band in United Kingdom conurbations. Results presented in this paper estimate that mesh networks at 868 MHz can accommodate large areas constituting several SMs with the proposed coverage extension method. With our findings and proposed methods on mesh connectivity, only 1% of UK premises will require mesh radios to achieve the desired coverage. [ABSTRACT FROM AUTHOR]

The homogeneous spatial Poisson point process (SPPP) is widely used for spatial modeling of mobile terminals (MTs). This process is characterized by a homogeneous distribution, complete spatial independence, and constant intensity measure. However, it is intuitive to understand that the locations of MTs are neither homogeneous, due to inhomogeneous terrain, nor independent, due to homophilic relations. Moreover, the intensity is not constant due to mobility. Therefore, assuming an SPPP for spatial modeling is too simplistic, especially for modeling realistic emerging device-centric frameworks such as device-to-device (D2D) communication. In this paper, assuming inhomogeneity, positive spatial correlation, and random intensity measure, we propose a doubly stochastic Poisson process, a generalization of the homogeneous SPPP, to model D2D communication. To this end, we assume a permanental Cox process (PCP) and propose a novel Euler-Characteristic-based approach to approximate the nearest-neighbor distribution function. We also propose a threshold and spatial distances from an excursion set of a chi-square random field as interference control parameters for different cluster sizes. The spatial distance of the clusters is incorporated into a Laplace functional of a PCP to analyze the average coverage probability of a cellular user. A closed-form approximation of the spatial summary statistics is in good agreement with empirical results, and its comparison with an SPPP authenticates the correlation modeling of D2D nodes. [ABSTRACT FROM AUTHOR]

In this paper, using the concept of stochastic geometry, we present an analytical framework to evaluate the signal-to-interference-and-noise-ratio (\textSINR ) coverage in the uplink of millimeter wave cellular networks. By using a distance-dependent line-of-sight (LOS) probability function, the location of LOS and nonLOS users are modeled as two independent nonhomogeneous Poisson point processes, with each having a different pathloss exponent. The analysis takes account of per-user fractional power control (FPC), which couples the transmission of users based on location-dependent channel inversion. We consider the following scenarios in our analysis: 1) pathloss-based FPC (PL-FPC) which is performed using the measured pathloss and 2) distance-based FPC (D-FPC) which is performed using the measured distance. Using the developed framework, we derive expressions for the area spectral efficiency and energy efficiency. Results suggest that in terms of \textSINR coverage, D-FPC outperforms PL-FPC scheme at high \textSINR where the future networks are expected to operate. It achieves equal or better area spectral efficiency and energy efficiency compared with the PL-FPC scheme. Contrary to the conventional ultra-high frequency cellular networks, in both FPC schemes, the \textSINR coverage decreases as the cell density becomes greater than a threshold, while the area spectral efficiency experiences a slow growth region. [ABSTRACT FROM PUBLISHER]

The popularity and convergence of wireless communications have resulted in continuous network upgrades to support the increasing demand for bandwidth. However, given that wireless communication systems operate on radio-frequency waves, the health effects of electromagnetic (EM) emission from these systems are increasingly becoming a concern due to the ubiquity of mobile communication devices. To address these concerns, we propose two schemes (offline and online) for minimizing the EM emission of users in the uplink of orthogonal frequency-division multiplexing (OFDM) systems, while maintaining an acceptable quality of service (QoS). We formulate our offline EM reduction scheme as a convex optimization problem and solve it through water filling. This is based on the assumption that the long-term channel state information (CSI) of all the users is known. Given that, in practice, long-term CSI of all the users cannot always be available, we propose our online EM emission reduction scheme, which is based on minimizing the instantaneous transmit energy per bit of each user. Simulation results show that both of our proposed schemes significantly minimize the EM emission when compared with the benchmark classic greedy spectral efficiency (SE)-based scheme and an energy efficiency (EE)-based scheme. Furthermore, our offline scheme proves to be very robust against channel prediction errors. [ABSTRACT FROM PUBLISHER]

The Mobile Internet connects billions of smart phones and laptops. With this global connectivity, the stage is set for the emergence of: (a)Tactile Internetto deliver haptic experiences to remote users, and (b) flexible and integratedBackhaul/Fronthaulnetworks to support demands of such applications. [ABSTRACT FROM AUTHOR]

In this paper, using stochastic geometry, we investigate the average energy efficiency (AEE) of the user terminal (UT) in the uplink of a two-tier heterogeneous network, where the two tiers are operated on separate carrier frequencies. In such a deployment, a typical UT must periodically perform the interfrequency small-cell discovery (ISCD) process to discover small cells in its neighborhood and benefit from the high data rate and traffic offloading opportunity that small cells present. We assume that the base stations of each tier and UTs are randomly located, and we derive the average ergodic rate and UT power consumption, which are later used for our AEE evaluation. The AEE incorporates the percentage of time that a typical UT missed small-cell offloading opportunity as a result of the periodicity of the ISCD process. The additional power consumed by the UT due to the ISCD measurement is also included. Moreover, we derive the optimal ISCD periodicity based on the UT's average energy consumption (AEC) and AEE. Our results reveal that ISCD periodicity must be selected with the objective of either minimizing the UT's AEC or maximizing the UT's AEE. [ABSTRACT FROM PUBLISHER]

We investigate the energy efficiency-spectral efficiency (EE-SE) trade-off of transmit antenna selection/maximum ratio combining (TAS) scheme. A realistic power consumption model (PCM) is considered, and it is shown that using TAS can provide significant energy savings when compared to multiple-input multiple-output (MIMO) in the low to medium SE region, regardless the number of antennas, as well as outperform transmit beamforming scheme (MRT) for the entire SE range. For a fixed number of receive antennas, our results also show that the EE gain of TAS over MIMO becomes even greater as the number of transmit antennas increases. The optimal value of SE that maximizes the EE is obtained analytically, and confirmed by numerical results. Moreover, the influence of receiver correlation is also evaluated and it is shown that considering a non-realistic PCM can lead to mistakes when comparing TAS and MIMO. [ABSTRACT FROM AUTHOR]

One of the major capacity boosters for 5G networks is the deployment of ultra-dense heterogeneous networks (UDHNs). However, this deployment results in a tremendous increase in the energy consumption of the network due to the large number of base stations (BSs) involved. In addition to enhanced capacity, 5G networks must also be energy efficient for it to be economically viable and environmentally friendly. Dynamic cell switching is a very common way of reducing the total energy consumption of the network, but most of the proposed methods are computationally demanding, which makes them unsuitable for application in ultra-dense network deployment with massive number of BSs. To tackle this problem, we propose a lightweight cell switching scheme also known as Threshold-based Hybrid cEll swItching Scheme (THESIS) for energy optimization in UDHNs. The developed approach combines the benefits of clustering and exhaustive search (ES) algorithm to produce a solution whose optimality is close to that of the ES (which is guaranteed to be optimal), but is computationally more efficient than ES and as such can be applied for cell switching in real networks even when their dimension is large. The performance evaluation shows that THESIS significantly reduces the energy consumption of the UDHN and can reduce the complexity of finding a near-optimal solution from exponential to polynomial complexity. [ABSTRACT FROM AUTHOR]

Virtual multiple-input–multiple-output (MIMO) systems using multiple antennas at the transmitter and a single antenna at each of the receivers have recently emerged as an alternative to point-to-point MIMO systems. This paper investigates the relationship between energy efficiency (EE) and spectral efficiency (SE) for a virtual-MIMO system that has one destination and one relay using compress-and-forward (CF) cooperation. To capture the cost of cooperation, the power allocation (between the transmitter and the relay) and the bandwidth allocation (between the data and cooperation channels) are studied. This paper derives a tight upper bound for the overall system EE as a function of SE, which exhibits good accuracy for a wide range of SE values. The EE upper bound is used to formulate an EE optimization problem. Given a target SE, the optimal power and bandwidth allocation can be derived such that the overall EE is maximized. Results indicate that the EE performance of virtual-MIMO is sensitive to many factors, including resource-allocation schemes and channel characteristics. When an out-of-band cooperation channel is considered, the performance of virtual-MIMO is close to that of the MIMO case in terms of EE. Considering a shared-band cooperation channel, virtual-MIMO with optimal power and bandwidth allocation is more energy efficient than the noncooperation case under most SE values. [ABSTRACT FROM PUBLISHER]

In this paper, we first develop an analytical framework for the total energy consumption of an amplify-and-forward (AF) multihop network employing M-ary quadrature amplitude modulation (MQAM) while satisfying an average bit error rate (BER) requirement at the destination over Rayleigh fading channels. Based on this framework, we then establish the conditions under which a dual-hop relay network is always more energy efficient when compared with a reference single-hop network. Moreover, the impact of the relay's location and the energy resource allocation between the relay and the source on the possible energy savings is also analyzed. Since a realistic power consumption model is considered, it is shown that there exists an optimal number of relays for the linear multihop relay network and that the maximum energy efficiency (EE) is obtained through the joint optimization of the number of relays and the constellation size. Considering this fact, we first formulate the optimization problem, and then, this problem is transformed into a convex form by relaxing constraints to be defined over the real numbers (instead of taking only discrete values). The new closed-form optimal solution that involves only elementary functions is derived for this relaxed problem. It is also demonstrated that the optimized multihop network has the potential not only to reduce the total energy consumption but to satisfy the peak-power constraint simultaneously at the expense of more delay as well. Finally, our analysis shows that significant energy savings are possible through joint optimization not only for delay-tolerant networks but for delay-limited networks as well, and up to about 55% energy savings are achievable over the optimized single-hop system. [ABSTRACT FROM PUBLISHER]

In this paper we analyze the energy efficiency of single-hop, multi-hop, cooperative selective decode-and-forward, cooperative incremental decode-and-forward, and even the combination of cooperative and non-cooperative schemes, in wireless sensor networks composed of several nodes. We assume that, as the sensor nodes can experience either non line-of-sight or some line-of-sight conditions, the Nakagami-m fading distribution is used to model the wireless environment. The energy efficiency analysis is constrained by a target outage probability and an end-to-end throughput. Our results show that in most scenarios cooperative incremental schemes are more energy efficient than the other methods. [ABSTRACT FROM AUTHOR]

In this paper, the trade-off between energy efficiency (EE) and spectral efficiency (SE) is analyzed for both the uplink and downlink of the distributed multiple-input multiple-output (DMIMO) system over the Rayleigh fading channel while considering different types of power consumption models (PCMs). A novel tight closed-form approximation of the DMIMO EE-SE trade-off is presented and a detailed analysis is provided for the scenario with practical antenna configurations. Furthermore, generic and accurate low and high-SE approximations of this trade-off are derived for any number of radio access units (RAUs) in both the uplink and downlink channels. Our expressions have been utilized for assessing both the EE gain of DMIMO over co-located MIMO (CMIMO) and the incremental EE gain of DMIMO in the downlink channel. Our results reveal that DMIMO is more energy efficient than CMIMO for cell edge users in both the idealistic and realistic PCMs; whereas in terms of the incremental EE gain, connecting the user terminal to only one RAU is the most energy efficient approach when a realistic PCM is considered. [ABSTRACT FROM AUTHOR]

Motivated by the increasing interest in energy-efficient communication systems, the relation between energy efficiency (EE) and spectral efficiency (SE) for multiple-input–multiple-output (MIMO) systems is investigated in this paper. To provide insights into the design of practical MIMO systems, we adopt a realistic power model and consider both independent Rayleigh fading and semicorrelated fading channels. We derived a novel and closed-form upper bound (UB) for the system EE as a function of SE. This UB exhibits great accuracy for a wide range of SE values and, thus, can be utilized for explicit assessment of the influence of SE on EE and for analytically addressing the EE optimization problems. Using this tight EE UB, our analysis unfolds two EE optimization issues: Given the number of transmit and receive antennas, an optimum value of SE is derived, such that the overall EE can be maximized, and given a specific value of SE, the optimal number of antennas is derived for maximizing the system EE. [ABSTRACT FROM AUTHOR]

Energy efficiency (EE) is undoubtedly an important criterion for designing power-limited systems, and yet in a context of global energy saving, its relevance for power-unlimited systems is steadily growing. Equally, resource allocation is a well-known method for improving the performance of cellular systems. In this paper, we propose an EE optimization framework for the downlink of planar cellular systems over frequency-selective channels. Relying on this framework, we design two novel low-complexity resource allocation algorithms for the single-cell and coordinated multi-cell scenarios, which are EE-optimal and EE-suboptimal, respectively. We then utilize our algorithms for comparing the EE performance of the classic non-coordinated, orthogonal and coordinated multi-cell approaches in realistic power and system settings. Our results show that coordination can be a simple and effective method for improving the EE of cellular systems, especially for medium to large cell sizes. Indeed, by using a coordinated rather than a non-coordinated resource allocation approach, the per-sector energy consumption and transmit power can be reduced by up to 15% and more than 90%, respectively. [ABSTRACT FROM PUBLISHER]

We compare the downlink energy efficiency of spatial diversity multiple transmit antenna schemes. We determine the minimum required transmit power for a given outage probability. Our analysis shows that antenna selection is in general the most energy efficient option as it requires a single radio-frequency chain. We also investigate the limiting distances up to which the antenna selection technique outperforms the transmit beamforming scheme for different numbers of transmit antennas. [ABSTRACT FROM PUBLISHER]

The race against climate change has been a great challenge for years, and the UK government has taken serious steps towards achieving the net-zero carbon target by 2050. Technology is leading the way and innovation is believed to be a key solution. Nevertheless, tackling the issue, by attempting to limit the waste in energy, due to negative energy usage behaviour, has proven to be a successful approach that is capable of complementing other technology-based initiatives. The first step towards this is to promote energy-conscious behaviour and pinpoint where savings can be made. Thereby, this paper contributes to the existing literature, by presenting a new methodology to identify potential energy waste and negative energy usage behaviour in an NHS hospital. The paper presents an analysis of electricity consumption vs occupancy during minimal consumption periods (i.e, bank holidays and weekends) and it presents a log of equipment left switched on outside of working hours, in order to highlight the level of energy-conscious behaviour. The results revealed that the proposed technique is not only able to identify negative energy usage behaviour amongst the hospital staff but helps identify areas where immediate energy savings can be made, with potential savings of more than 30,000 pounds, if action is taken. [ABSTRACT FROM AUTHOR]

Flying ad hoc network (FANET) is a self-organizing wireless network that enables inexpensive, flexible, and easy-to-deploy flying nodes, such as unmanned aerial vehicles (UAVs), to communicate among themselves in the absence of fixed network infrastructure. FANET is one of the emerging networks that has an extensive range of next-generation applications. Hence, FANET plays a significant role in achieving application-based goals. Routing enables the flying nodes to collaborate and coordinate among themselves and to establish routes to radio access infrastructure, particularly FANET base station (BS). With a longer route lifetime, the effects of link disconnections and network partitions reduce. Routing must cater to two main characteristics of FANETs that reduce the route lifetime. Firstly, the collaboration nature requires the flying nodes to exchange messages and to coordinate among themselves, causing high energy consumption. Secondly, the mobility pattern of the flying nodes is highly dynamic in a three-dimensional space and they may be spaced far apart, causing link disconnection. In this paper, we present a comprehensive survey of the limited research work of routing schemes in FANETs. Different aspects, including objectives, challenges, routing metrics, characteristics, and performance measures, are covered. Furthermore, we present open issues. [ABSTRACT FROM AUTHOR]

Presents corrections made to the paper, ?Energy Efficiency-Spectral Efficiency Trade-Off of Transmit Antenna Selection? (Rayel, O.K., et al; IEEE Trans. Commun., vol. 62, no. 12, pp. 4293?4303, Dec. 2014). [ABSTRACT FROM PUBLISHER]

Along with spectral efficiency (SE), energy efficiency (EE) is becoming one of the key performance evaluation criteria for communication system. These two criteria, which are conflicting, can be linked through their trade-off. The EE-SE trade-off for the multi-input multi-output (MIMO) Rayleigh fading channel has been accurately approximated in the past but only in the low-SE regime. In this paper, we propose a novel and more generic closed-form approximation of this trade-off which exhibits a greater accuracy for a wider range of SE values and antenna configurations. Our expression has been here utilized for assessing analytically the EE gain of MIMO over single-input single-output (SISO) system for two different types of power consumption models (PCMs): the theoretical PCM, where only the transmit power is considered as consumed power; and a more realistic PCM accounting for the fixed consumed power and amplifier inefficiency. Our analysis unfolds the large mismatch between theoretical and practical MIMO vs. SISO EE gains; the EE gain increases both with the SE and the number of antennas in theory, which indicates that MIMO is a promising EE enabler; whereas it remains small and decreases with the number of transmit antennas when a realistic PCM is considered. [ABSTRACT FROM AUTHOR]

In this paper, we propose novel Hybrid Automatic Repeat re-Quest (HARQ) strategies used in conjunction with hybrid relaying schemes, named as H^2-ARQ-Relaying. The strategies allow the relay to dynamically switch between amplify-and-forward/compress-and-forward and decode-and-forward schemes according to its decoding status. The performance analysis is conducted from both the spectrum and energy efficiency perspectives. The spectrum efficiency of the proposed strategies, in terms of the maximum throughput, is significantly improved compared with their non-hybrid counterparts under the same constraints. The consumed energy per bit is optimized by manipulating the node activation time, the transmission energy and the power allocation between the source and the relay. The circuitry energy consumption of all involved nodes is taken into consideration. Numerical results shed light on how and when the energy efficiency can be improved in cooperative HARQ. For instance, cooperative HARQ is shown to be energy efficient in long distance transmission only. Furthermore, we consider the fact that the compress-and-forward scheme requires instantaneous signal to noise ratios of all three constituent links. However, this requirement can be impractical in some cases. In this regard, we introduce an improved strategy where only partial and affordable channel state information feedback is needed. [ABSTRACT FROM PUBLISHER]

Smart energy performance monitoring and optimisation at the supplier and consumer levels is essential to realising smart cities. In order to implement a more sustainable energy management plan, it is crucial to conduct a better energy forecast. The next-generation smart meters can also be used to measure, record, and report energy consumption data, which can be used to train machine learning (ML) models for predicting energy needs. However, sharing energy consumption information to perform centralised learning may compromise data privacy and make it vulnerable to misuse, in addition to incurring high transmission overhead on communication resources. This study addresses these issues by utilising federated learning (FL), an emerging technique that performs ML model training at the user/substation level, where data resides. We introduce FedraTrees, a new, lightweight FL framework that benefits from the outstanding features of ensemble learning. Furthermore, we developed a delta-based FL stopping algorithm to monitor FL training and stop it when it does not need to continue. The simulation results demonstrate that FedraTrees outperforms the most popular federated averaging (FedAvg) framework and the baseline Persistence model for providing accurate energy forecasting patterns while taking only 2% of the computation time and 13% of the communication rounds compared to FedAvg, saving considerable amounts of computation and communication resources. [ABSTRACT FROM AUTHOR]