Capacity and energy efficiency analysis of dense HetNets with biasing

Very recent studies showed that in a fully loaded dense small cell network (SCN), the coverage probability performance will continuously decrease with the network densification. Such new results were captured in IEEE ComSoc Technology News with an alarming title of “Will Densification Be the Death of 5G?” In this paper, we revisit this issue from more practical views of realistic network deployment, such as a finite number of active base stations (BSs) and user equipments (UEs), a decreasing BS transmission power with the network densification, etc. Particularly, in dense SCNs, due to an oversupply of BSs with respect to UEs, a large number of BSs can be put into idle modes without signal transmission, if there is no active UE within their coverage areas. Setting those BSs into idle modes mitigates unnecessary intercell interference and reduces energy consumption. In this paper, we investigate the performance impact of such BS idle mode capability (IMC) on dense SCNs. Different from existing work, we consider a realistic path loss model incorporating both line-of-sight (LoS) and non-LoS transmissions. Moreover, we obtain analytical results for the coverage probability, the area spectral efficiency and the energy efficiency (EE) performance for SCNs with the BS IMC and show that the performance impact of the IMC on dense SCNs is significant. As the BS density surpasses the UE density in dense SCNs, the coverage probability will continuously increase toward one , addressing previous concerns on “the death of 5G”. Finally, the performance improvement in terms of the EE performance is also investigated for dense SCNs using practical energy models developed in the Green-Touch project.

The explosive growth of mobile date traffic and ubiquitous mobile services cause an high energy consumption in mobile devices with limited energy supplies, which has become a bottleneck for deploying device-to-device (D2D) communication. Simultaneous wireless information and power transfer (SWIPT), which enables mobile devices to harvest energy from the radio frequency signals, has emerged as a promising solution to improve the energy efficiency (EE) performance. In this paper, we address joint power control and spectrum resource allocation problem in SWIPT-based energy-harvesting D2D underlay networks. First, we formulate joint optimization problem as a 2-D matching between D2D pairs and cellular user equipments (CUEs), and propose a preference establishment algorithm based on Dinkelbach method and Lagrange dual decomposition. Second, we propose an energy-efficient stable matching algorithm by exploring the Gale-Shapley algorithm, which is able to maximize the EE performance of D2D pairs and the amount of energy harvested by CUEs simultaneously. Third, we provide in-depth theoretical analysis of the proposed matching algorithm in terms of stability, optimality, and complexity. Simulation results demonstrate that the proposed algorithm can bring significant EE performance gains compared with some heuristic algorithms.

The use of electric vehicles (EVs) has recently increased in a smart city environment. With this, the optimal location of the charging station is a great challenge and, hence, the energy efficiency performance (EEP) of an electrical system is important. Ideally, the EEP is realized through passive energy boosters (PEBs) and active energy boosters (AEBs). PEBs require no external resources, and EEP is achieved through altering the network topology and loading patterns, whereas, in AEBs, integrating external energy resources is a must. The EEP has also become dynamic with the integration of an energy storage system (ESS) in a deregulated environment. Customer energy requirement varies daily, weekly, and seasonally. In this scenario, the frequent change in network topology requires modifying the size and location of AEBs. It alters the customers’ voltage profile, loadability margin, and supply reliability when the EV works differently as a load or source. Therefore, a comprehensive EEP analysis with different probabilistic loading patterns, including ESS, must be performed at the planning stage. This work uses a harmony search algorithm to evaluate EEP for AEBs and PEBs, in coordination, when ESS works as a load or source, at four locations, for customers’ and utilities’ benefits.

With the explosive increase of mobile data and users, data tsunami seriously challenges the mobile operators worldwide. The vehicular caching, which caches mobile data on widely distributed vehicles, is an efficient method to solve this problem. In this paper, we explore the impact of vehicular caching on cellular networks. Specifically, targeting on network performance in energy efficiency, we first formulate a fractional optimization model by considering the network throughput and energy consumption. We then apply nonlinear programming and Lyapunov technology to relax the nonlinear and nonconvex model. Based on analysis, we propose a novel online task decision algorithm. Based on this algorithm, vehicles determine to act either as servers or task schedulers for the requests of users. The burden of cellular MBS (Macro Base Station) then can be alleviated. Extensive simulations are finally conducted and results verify the effectiveness of our proposal.

Energy efficiency (EE) is considered as one of the pivotal uplink (UL) performance metrics for 5G dense networks. It consists of two conflicting objectives that are recognised as benefit-cost ratio: spectral efficiency and energy consumption. Accordingly, network design tradeoff is the key challenge for future networks. In this paper, we aim to jointly maximise network spectral efficiency and minimise power consumption with respect to the following design parameters: base station (BS) density, users' number, equipped antennas' number, and signal-to-noise power ratio without losing service quality. The performance of the ultra-dense network is characterised on the basis of the Pareto optimality concept through the following benchmarks: (i) studying impact of exhausted power on the deployed hardware elements. (ii) Validating the total EE performance through Monte-Carlo simulation within a low cost of processing time. (iii) The proposed approach is compared against single objective scheme to show the significance of the design tradeoff. Furthermore, we will introduce a detailed mathematical analysis for UL power policy and channel estimation for reliable pilot reusing. Simulation results will show that our proposed solution guarantee remarkable EE performance via reducing the number of deployed BSs without scarificing service quality.

Energy efficiency (EE) performance of millimeter-wave (mmWave) large-array systems attracts a lot of attention. And insertion loss is an inherent characteristic of hybrid precoding systems, which greatly reduces the system performance. EE analysis considering the insertion loss based on the dynamic array architecture is still an open issue. This paper researches the ergodic EE of mmWave hybrid pre-coding system with the insertion loss, based on the adaptive overlapped subarray (OSA) architecture. The ergodic EE is a more valuable indicator than the instantaneous EE for the system under dynamic architecture. However, it is difficult to directly calculate the precise ergodic EE due to the intractable relationship between EE and the channel matrix. Instead, we simplify the precise ergodic EE to get a lower bound, and analyze the ergodic EE performance based upon the lower bound. By this way, we analyze the ergodic EE performance of two typical hybrid pre-coding schemes taking the dynamic architectures. Simulation results verify the effectiveness of analyses.

In this paper, we design a resource allocation (RA) scheme for the downlink of relay-assisted orthogonal frequency division multiple access cellular networks. Our design goal is to maximize the energy efficiency (EE) with minimal signaling overhead and low computational complexity. To alleviate the signaling overhead of channel information, the proposed scheme allocates the resources in a distributed manner, where each relay station (RS) or base station (BS) individually performs a joint subchannel and power allocation for its subordinate users. To increase the cell throughput, the proposed scheme allows the subchannel reuse among RSs and this enhances the EE performance. The proposed scheme is composed of the resource allocation at RS (RS-RA) and the resource allocation at BS (BS-RA). The RS-RA is formulated as an optimization problem that minimizes the consumed power of RS while reusing as many subchannels as possible among RSs. The optimization objective of BS-RA is to maximize the EE of the cell. Simulation results show that the proposed distributed RA scheme achieves remarkably excellent EE performance with small signaling overhead, comparable with the centralized optimal RA scheme aiming at the EE maximization based on full channel information.

Environmental Investment and Firm Performance: A Panel VAR Approach

In this paper, we first give an overview of the coexistence of cellular with IEEE 802.11 technologies in the unlicensed bands. We then present a coexistence mechanism for Fifth‐Generation (5G) New Radio on Unlicensed (NR‐U) small cells located within buildings to coexist with the IEEE 802.11ad/ay, also termed as Wireless Gigabit (WiGig). Small cells are dual‐band enabled operating in the 60 GHz unlicensed and 28 GHz licensed millimeter‐wave (mmW) bands. We develop an interference avoidance scheme in the time domain to avoid cochannel interference (CCI) between in‐building NR‐U small cells and WiGig access points (APs). We then derive average capacity, spectral efficiency (SE), and energy efficiency (EE) performance metrics of in‐building small cells. Extensive system‐level numerical and simulation results and analyses are carried out for a number of variants of NR‐U, including NR standalone, NR‐U standalone, and NR‐U anchored. We also analyze the impact of the spatial reuse of both mmW spectra of multiple NR‐U anchored operators with a WiGig operator. It is shown that NR‐U anchored provides the best average capacity and EE performances, whereas NR‐U standalone provides the best SE performance. Moreover, both vertical spatial reuse intrabuilding level and horizontal spatial reuse interbuilding level of mmW spectra in small cells of an NR‐U anchored can improve its SE and EE performances. Finally, we show that by choosing appropriate values of vertical and horizontal spatial reuse factors, the proposed coexistence mechanism can achieve the expected SE and EE requirements for the future Sixth‐Generation (6G) mobile networks.

Co-operative communication has been shown to significantly improve energy efficiency in wireless sensor networks. The outdated channel state information (CSI) problem will result in severe performance degradation of co-operative communication systems including energy efficiency. In this study, the authors analyse the impact of outdated CSI on energy efficiency of amplify-and-forward co-operative hybrid automatic repeat reQuest system. The authors derive the expression of the average energy consumption per bit of data transmission under outdated CSI. Numerical results show the deteriorating effects of outdated CSI on the performance of energy efficiency and transmission reliability in co-operative communication system. It is also shown that energy efficiency can be improved by error correcting codes mechanism when end-to-end signal-to-noise ratio at the destination node is within a certain range.

This paper studies the energy efficiency (EE) of the cloud radio access network (C-RAN), consisting of multiple remote radio heads (RRHs) equipped with electronically steerable parasitic array radiator (ESPAR) antennas, which provide multiple antenna functionality with a single radio frequency (RF) chain. An EE optimization problem is formulated to obtain the configuration of ESPAR and the closed-form expressions of the voltage feeding and the loadings are derived for signal transmission at each RRH. Specifically, we obtain the closed-form expressions for precoder and power allocation that are applicable not only for the ESPAR based system but also for standard MIMO antenna (SMA) system with multiple RF chains. It is shown that EA system can be configured with less complexity compared with SMA system in block fading channel. Furthermore, symbol error rate (SER) and EE performances are compared for EA and SMA based systems. It is shown that the system with EA provides better EE performance while providing similar SER performance. From our results, it is proved that EA system can provide better performance to satisfy the requirement of 5G wireless communication networks.

Thermoelectric (TE) generation is becoming a valuable and promising research direction. Many researchers have carried out system analysis and performance optimization of thermoelectric technologies based on the generalized thermoelectric energy balance equations. However, it is assumed that TE legs have no heat exchange with the ambient except at the junctions of the hot and cold ends where heat flows in and out. Based on basic thermoelectric effects and fundamental theories of heat transfer, a detailed derivation of the revised generalized thermoelectric energy equations considering convective heat transfer between TE legs and the ambient has been carried out. Irreversible heat transfer processes have been analyzed by employing energy analysis based on the first law of thermodynamics and exergy analysis based on the second law of thermodynamics. The results show that convective heat transfer leads to a decrease in both energy and exergy efficiencies: the rate and magnitude of the decrease in exergy efficiency are greater than those of the decrease in energy efficiency. The exergy efficiency is relatively high despite the low energy efficiency in operation, revealing the features and advantages of thermoelectric generators (TEGs) in low‐grade energy utilization. For TEG efficient operation, the load resistance value should match the system's internal resistance, or at least be greater than that, to avoid a sharp drop in power output and efficiencies. In an attempt at theoretical analysis, the concept of entransy was first introduced into thermoelectric analysis, yielding two concise relational equations which reflect the intrinsic link between Carnot cycle efficiency, energy efficiency, exergy efficiency, and entransy flow transfer efficiency. The entransy analysis based on the index of entransy flow transfer efficiency, together with energy analysis and exergy analysis, may be a novel and valuable guideline for the operation and optimization of TEGs, which needs to be further investigated.

The growing popularity of high-speed mobile communications, cloud computing, and the Internet of Things (IoT) has reinforced the tidal traffic phenomenon, which induces spatio-temporal disequilibrium in the network traffic load. The main reason for tidal traffic is the large-scale population migration between business areas during the day and residential areas during the night. Traffic grooming provides an effective solution to aggregate multiple fine-grained IP traffic flows into the optical transport layer by flexibly provisioning lightpaths over the physical topology. In this paper, we introduce a comprehensive study on energy efficiency and network performance enhancement in the presence of tidal traffic. We propose and leverage the concept of stateful grooming to apply differentiated provisioning policies based on the state of network nodes. We formulate and solve the node-state-decision optimization problem, which can decide the specific state of network nodes when a certain traffic profile is given, considering the trade-off between energy efficiency and blocking performance with a multi-objective integer linear program (MOILP). Then, we propose an online traffic-aware intelligent differentiated allocation of lightpaths (TIDAL) algorithm, based on stateful grooming and the MOILP, to accommodate the dynamic tidal traffic. Our illustrative numerical results show that the proposed method can achieve a significant performance improvement in an energy-efficient way.

Energy use and energy efficiency development in the German and Colombian textile industries

This paper studies the energy efficiency (EE) optimization of a single-cell multiuser massive multiple-input multiple-output (MIMO) uplink system, where configurable dy-namic metasurface antennas (DMAs) are deployed at the base station (BS). To maximize the system EE, we present a framework for the joint optimization of the users' transmit precoding and the BS DMAs' weights, which is based on Dinkelbach's transform and an alternating optimization algorithm. Since the physical structure constraint of DMAs exhibits a non-convex form, we firstly obtain the optimal unconstrained DMAs' weights in closed form. Then, we configure those weights with the non-convex constraint and approximate them with the optimal unconstrained solutions. Our numerical results showcase that our DMAs-based systems can achieve much higher EE performance than those based on conventional antenna arrays and beamforming architectures. It is also demonstrated that the EE performance of DMAs-based uplink massive MIMO systems can be further improved by adjusting the number of microstrips and the number of meta-atoms per microstrip.