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Simultaneous wireless information and power transmission (SWIPT) allows the use of RF signals for both information detection and energy harvesting. Integration of cooperation, NOMA and SWIPT can provide energy-efficient, reliable, and spectral-efficient networks. Therefore, this study aims to design energy harvesting-enabled cooperative NOMA (C-NOMA) networks. This work investigates relay selection for multiple relay downlink C-NOMA networks with SWIPT in the presence of interference. The analytical closed-form outage probability expressions for the proposed relay selection are derived. Subsequently, the impact of various parameters, including the number of available relay nodes, energy harvesting parameters, and energy conversion efficiency, is analyzed on the performance of proposed networks. The finding showed that system performance improves with the number of intermediate relaying nodes, transmit power, and energy conversion efficiency. Comparative analysis of NOMA and time division multiple access TDMA proved the superiority of NOMA over traditional OMA schemes. [ABSTRACT FROM AUTHOR]

The sixth-generation (6G) wireless cellular network integrates several wireless bands and modes with the objectives of improving quality of service (QoS) and increasing network connectivity. The 6G environment includes asymmetrical heterogeneous networks (HetNets) with the intention of making effective use of the available frequencies. However, selecting a suitable gNB and a communication channel that works for users in the network is an enormous challenge in 6G HetNets. This paper investigates a joint user association (UA) and channel allocation (CA) problem in two-tier HetNets by considering the downlink scenario to improve QoS. Our study presents an innovative scheme for user association and channel allocation, wherein the user can be connected to either the macro base station (MBS) or a possible small base station (SBS) in a direct or relay-assisted link. Furthermore, the proposed scheme identifies the optimal channel to be allocated to each user so that the overall network QoS can be maximized. A symmetric matching game-based user association is proposed to find the optimal association for users. Moreover, a modified auction game is applied to allocate the optimal channel by considering the quota of each gNB. Regarding connection probability, throughput, energy efficiency (EE), and spectrum efficiency (SE), the simulation results show that the proposed approach performs well over the state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

The tremendous advancement in distributed computing and Internet of Things (IoT) applications has resulted in the adoption of fog computing as today’s widely used framework complementing cloud computing. Thus, suitable and effective applications could be performed to satisfy the applications’ latency requirement. Resource allocation techniques are essential aspects of fog networks which prevent unbalanced load distribution. Effective resource management techniques can improve the quality of service metrics. Due to the limited and heterogeneous resources available within the fog infrastructure, the fog layer’s resources need to be optimised to efficiently manage and distribute them to different applications within the IoT network. There has been limited research on resource management strategies in fog networks in recent years, and a limited systematic review has been done to compile these studies. This article focuses on current developments in resource allocation strategies for fog-IoT networks. A systematic review of resource allocation techniques with the key objective of enhancing QoS is provided. Steps involved in conducting this systematic literature review include developing research goals, accessing studies, categorizing and critically analysing the studies. The resource management approaches engaged in this article are load balancing and task offloading techniques. For the load balancing approach, a brief survey of recent work done according to their sub-categories, including stochastic, probabilistic/statistic, graph theory and hybrid techniques is provided whereas for task offloading, the survey is performed according to the destination of task offloading. Efficient load balancing and task-offloading approaches contribute significantly to resource management, and tremendous effort has been put into this critical topic. Thus, this survey presents an overview of these extents and a comparative analysis. Finally, the study discusses ongoing research issues and potential future directions for developing effective management resource allocation techniques. [ABSTRACT FROM AUTHOR]

Establishing a wireless communication network (WCN) is critical to saving people's lives during disasters. Since the user equipment (UE) must transfer their information to the functioning area, their batteries will be significantly drained. Thus, technologies that can compensate for battery power consumption, such as the energy harvesting (EH) strategy, are highly required. This paper proposes a framework that employs EH at the main cluster head (MCH) selected by the enhanced clustering technique (CFT) and simultaneously transmits information and power wirelessly to prolong the lifetime of the energy-constrained network. MCH harvests energy from the radio frequency signal via the relay station (RS) and uses the harvested energy for D2D communications. The suggested framework was evaluated by analyzing the EH outage probability and estimating the energy efficiency performance, which is expected to improve the stability of the network. Compared to the UAV scenario, the simulation findings show that when RS is in its optimal location, it enhances the network EH outage probability performance by 26.3%. Finally, integrating CFT with wireless communications links into cellular networks is an effective technique for maintaining communication services for mission-critical applications. [ABSTRACT FROM AUTHOR]

Future wireless communication networks will be largely characterized by small cell deployments, typically on the order of 200 meters of radius/cell, at most. Meanwhile, recent studies show that base stations (BS) account for about 80 to 95 % of the total network power. This simply implies that more energy will be consumed in the future wireless network since small cell means massive deployment of BS. This phenomenon makes energy-efficient (EE) control a central issue of critical consideration in the design of future wireless networks. This paper proposes and investigates (the performance of) two different energy-saving approaches namely, adaptive-sleep sectorization (AS), adaptive hybrid partitioning schemes (AH) for small cellular networks using smart antenna technique. We formulated a generic base-model for the above-mentioned schemes and applied the spatial Poisson process to reduce the system complexity and to improve flexibility in the beam angle reconfiguration of the adaptive antenna, also known as a smart antenna (SA). The SA uses the scalable algorithms to track active users in different segments/sectors of the microcell, making the proposed schemes capable of targeting specific users or groups of users in periods of sparse traffic, and capable of performing optimally when the network is highly congested. The capabilities of the proposed smart/adaptive antenna approaches can be easily adapted and integrated into the massive MIMO for future deployment. Rigorous numerical analysis at different orders of sectorization shows that among the proposed schemes, the AH strategy outperforms the AS in terms of energy saving by about 52 %. Generally, the proposed schemes have demonstrated the ability to significantly increase the power consumption efficiency of micro base stations for future generation cellular systems, over the traditional design methodologies. [ABSTRACT FROM AUTHOR]

In order to mitigate the power consumption issue for the sensor's nodes, an efficient power optimized routing protocol is needed. Therefore, this paper proposes a network coding backpressure routing (NCBPR) routing scheme for a large-scale Internet of Things (IoT) networks, which exploits the backpressure algorithm in order to divert packets flow. In the network, the packets are flowing from the highly congested node to low congested node, which helps to balance the load and optimized the fair use of the battery power of all the participating nodes. It divides the network into the small clusters, where the selection of clusters head depends upon an additional parameter of battery power apart from other optimum path parameters. It also employs an efficient data aggregation mechanism, which improves the throughput of the network by eliminating redundant packets. The network has been designed by considering 300 nodes in a network and the results have been drawn in terms of network throughput, packet delivery ratio and energy consumption. The results are presented in comparison with conventional well-known information-fusion-based role assignment (InFRA) and data routing for in-network aggregation (DRINA) routing schemes. The results prove that the proposed NCBPR scheme delivers significant improvement, such as throughput which increased by 21.38 and 12.13%, packet delivery ratio improved by 24.73 and 11.38%, and sensors node's energy consumption is decreased by 61.46 and 44.35% as compared to conventional InFRA and DRINA schemes, respectively. [ABSTRACT FROM AUTHOR]

In Mobile Ad hoc Networks (MANETs), nodes' mobility, traffic congestion, and link quality estimation of the intermediate nodes are very crucial factors for establishing a reliable forwarding path between a source and destination node pairs. The unpredictable movement of nodes and random data traffic flow at a single node can cause congestion and network topology instability, which significantly lowers the performance of the ad hoc network. Indeed, the above-highlighted issues can be mitigated by implementing a more reliable mobility-centric, contention, and link quality-aware routing protocol for efficient data transmissions in a mobile network. This paper proposes a routing strategy called Mobility, Contention window, and Link quality sensitive multipath Routing (MCLMR) in MANETs, which considers the nodes mobility, contention window size, and link quality estimated value of the intermediate nodes in the optimal route selection. Also, Technique for Order of Preference by Similarity to Ideal Solution; a multicriteria decision-making technique, which provides weights according to node mobility, contention window size, and link quality estimated values, is also employed for the selection of intermediate nodes, whereas the Expected Number of Transmissions metric is used to minimize the effect of control message storm. The extensive simulations results prove that the proposed MCLMR routing scheme outperforms the conventional Multipath Optimized Link State Routing (MP-OLSR) and MP-OLSRv2 routing schemes in terms of network throughput, end-to-end delay, energy consumption, and packets loss ratio. [ABSTRACT FROM AUTHOR]

In this paper, we propose a data aggregation back pressure routing (DABPR) scheme, which aims to simultaneously aggregate overlapping routes for efficient data transmission and prolong the lifetime of the network. The DABPR routing algorithm is structured into five phases in which event data is sent from the event areas to the sink nodes. These include cluster-head selection, maximization of event detection reliability, data aggregation, scheduling, and route selection with multi attributes decision making metrics phases. The scheme performs data aggregation on redundant data at relay nodes in order to decrease both the size and rate of message exchanges to minimize communication overhead and energy consumption. The proposed scheme is assessed in terms of packet delivery, network lifetime, ratio, energy consumption, and throughput, and compared with two other well-known protocols, namely "information-fusion-based role assignment (InFRA)" and "data routing for in-network aggregation (DRINA)", which intrinsically are cluster and tree-based routing schemes designed to improve data aggregation efficiency by maximizing the overlapping routes. Meticulous analysis of the simulated data showed that DABPR achieved overall superior proficiency and more reliable performance in all the evaluated performance metrics, above the others. The proposed DABPR routing scheme outperformed its counterparts in the average energy consumption metric by 64.78% and 51.41%, packet delivery ratio by 28.76% and 16.89% and network lifetime by 42.72% and 20.76% compared with InFRA and DRINA, respectively. [ABSTRACT FROM AUTHOR]

Spectrum scarcity is a major challenge in wireless communications systems requiring efficient usage and utilization. Cognitive radio network (CRN) is found as a promising technique to solve this problem of spectrum scarcity. It allows licensed and unlicensed users to share the same licensed spectrum band. Interference resulting from cognitive radios (CRs) has undesirable effects on quality of service (QoS) of both licensed and unlicensed systems where it causes degradation in received signal-to-noise ratio (SIR) of users. Power control is one of the most important techniques that can be used to mitigate interference and guarantee QoS in both systems. In this paper, we develop a new approach of a distributed power control for CRN based on utility and pricing. QoS of CR user is presented as a utility function via pricing and a distributed power control as a non-cooperative game in which users maximize their net utility (utility-price). We define the price as a real function of transmit power to increase pricing charge of the farthest CR users. We prove that the power control game proposed in this study has Nash Equilibrium as well as it is unique. The obtained results show that the proposed power control algorithm based on a new utility function has a significant reduction in transmit power consumption and high improvement in speed of convergence. [ABSTRACT FROM AUTHOR]

The fog radio access network (F-RAN) is considered an efficient architecture for caching technology as it can support both edge and centralized caching due to the backhauling of the fog access points (F-APs). Successful transmission probability (STP), delay, and energy efficiency (EE) are key performance metrics for F-RAN. Therefore, this paper proposes a proactive cache placement scheme that jointly optimizes STP, delay, and EE in wireless backhauled cache-enabled F-RAN. First, expressions of the association probability, STP, average delay, and EE are derived using stochastic geometry tools. Then, the optimization problem is formulated to obtain the optimal cache placement that maximizes the weighted sum of STP, EE, and negative delay. To solve the optimization problem, this paper proposes the normalized cuckoo search algorithm (NCSA), which is a novel modified version of the cuckoo search algorithm (CSA). In NCSA, after generating the solutions randomly via Lévy flight and random walk, a simple bound is applied, and then the solutions are normalized to assure their feasibility. The numerical results show that the proposed joint cache placement scheme can effectively achieve significant performance improvement by up to 15% higher STP, 45% lower delay, and 350% higher EE over the well-known benchmark caching schemes. [ABSTRACT FROM AUTHOR]