Multi-hop Communication Research Articles

ARMS‐EGR—Adaptive ranking and mobile sink‐enabled energy‐efficient geographic routing protocol in flying ad hoc networks

SummaryUnmanned aerial vehicles (UAVs) have become widespread because of their involvement in a variety of applications. The task of designing the energy‐efficient routing between UAVs has been considered a matter of great interest due to the inherent challenges of controlling the dynamics exhibited by UAVs. Energy limitations are considered the main limitations of UAVs. This research paper proposes a novel routing protocol, adaptive ranking and mobile sink (MS)‐enabled energy‐efficient geographic routing (ARMS‐EGR) for flying ad hoc networks. In ARMS‐EGR, the whole network is partitioned into cells. The cell contains cell members (CM) and cell heads (CHs). The CH works as a cluster head. Additionally, two MSs have been used to collect data captured by CM. Multihop communication on the network leads to an increase in traffic and consumes the energy of the UAVs located near the base station (BS). MSs are used for power distribution and load balancing across the network. Adaptive ranking of forwarder UAVs and CHs is performed during intracell and intercell multihop communication, respectively, using adaptive ranking. A cell with one‐hop communication can directly send packets to the MS, but the ARMS‐EGR routing protocol has been proposed for multihop communication. The proposed approach is simulated in NS‐2.35 software. The results show that end‐to‐end latency and power consumption during packet transmission are greatly minimized. ARMS‐EGR also demonstrates improvements in message success rates, number of alive nodes, and packet delivery ratio, making ARMS‐EGR particularly suitable for flying ad hoc networks (FANETs).

MRT-LoRa: A multi-hop real-time communication protocol for industrial IoT applications over LoRa networks

Recent literature proposed MAC protocols running on top of LoRa that are able to offer real-time communications for Industrial Internet of Things (IIoT) applications. However, such solutions work over single-hop star topologies and therefore, to reach a wide coverage through a single hop, they require to configure the LoRa radio parameters in a way that reduces the maximum supported bit rate, thus increasing the message time on air. Consequently, to comply with the maximum duty cycle constraints imposed on LoRa devices by the current regulations, the maximum number of messages that can be sent per hour is also reduced. However, industrial environments typically cover very large areas and require bit rate values in the order of a few thousands of bits per second for LoRa-based networks. To cope with both coverage and bit rate requirements of IIoT, a multi-hop protocol able to provide bounded delays to the real-time flows typical of industrial applications is a better solution than a single-hop approach. For this reason, this paper proposes MRT-LoRa, a multi-hop communication protocol running on top of LoRa that provides support for real-time flows. The MRT-LoRa protocol enables long-range communications while maintaining shorter time on air at each hop, thus lowering the impact on the duty cycle of each node. The paper describes the MRT-LoRa design and configuration, and discusses the performance obtained through OMNeT++ simulations in realistic industrial IoT scenarios.

An Improved Routing Approach for Enhancing QoS Performance for D2D Communication in B5G Networks

Device-to-device (D2D) communication is one of the eminent promising technologies in Beyond Fifth Generation (B5G) wireless networks. It promises high data rates and ubiquitous coverage with low latency, energy, and spectral efficiency among peer-to-peer users. These advantages enable D2D communication to be fully realized in a multi-hop communication scenario. However, to ideally implement multi-hop D2D communication networks, the routing aspect should be thoroughly addressed since a multi-hop network can perform worse than a conventional mobile system if wrong routing decisions are made without proper mechanisms. Thus, routing in multi-hop networks needs to consider device mobility, battery, link quality, and fairness, which issues do not exist in orthodox cellular networking. Therefore, this paper proposed a mobility, battery, link quality, and contention window size-aware routing (MBLCR) approach to boost the overall network performance. In addition, a multicriteria decision-making (MCDM) method is applied to the relay devices for optimal path establishment, which provides weights according to the evaluated values of the devices. Extensive simulation results under various device speed scenarios show the advantages of the MBLCR compared to conventional algorithms in terms of throughput, packet delivery ratio, latency, and energy efficiency.

An Adaptive QoS and Trust-Based Lightweight Secure Routing Algorithm for WSNs

The limited resources and low computational power of wireless sensor networks (WSNs) make them vulnerable to various security attacks. Conventional security mechanisms require too many resources to allow the reliable operation of WSNs due to their resource-constrained nature. In addition, multihop communication in WSNs creates a requirement for guaranteed Quality of Service (QoS). Therefore, providing security while maintaining QoS and energy efficiency in WSNs are important design considerations. To further increase the performance of WSNs, there is a need to overcome the energy-hole problem, which leads to poor coverage of the field of interest. An energy-hole problem is created because of using poor deployment strategies. In this article, we define a multiobjective WSN optimization problem and present a novel algorithm known as lightweight secure routing (LSR) to manage WSNs that directly addresses the multiobjective WSN optimization problem. Our LSR algorithm uses ant colony optimization (ACO), an adaptive security model based on direct and indirect trust calculations, an adaptive QoS model, a hybrid deployment model based on 2-D Gaussian and uniform distributions, and an adaptive connectivity model that uses an appropriate communicational radius to ensure high connectivity between sensor nodes to solve the multiobjective WSN optimization problem. We divide our simulation results into three analyses, namely, trust model analysis, network scalability analysis, and security risk analysis to show that LSR outperforms the existing techniques in terms of energy consumed to calculate trust values, trust values convergence, network lifetime, average routing delay, and packet delivery ratio.

SF-Partition-Based Clustering and Relaying Scheme for Resolving Near–Far Unfairness in IoT Multihop LoRa Networks

Long range (LoRa) is one of the most successful low-power wide-area networking technologies because it is ideally suited for long-distance, low-bit rate, and low-power communications in the unlicensed sub-GHz spectrum utilized for Internet of things (IoT) networks. The effectiveness of LoRa depends on the link budget (i.e., spreading factor (SF), bandwidth (BW), and transmission power (TX)). Due to the near-far effect, the allocation of a link budget to LoRa devices (LDs) in large coverage regions is unfair between them depending on their distance to the GW. Thus, more transmission opportunities are given to some LDs to the detriment of other LD's opportunities. Numerous studies have been conducted to address the prevalent near-far fairness problem. Due to the absence of a tractable analytical model for fairness in the LoRa network, however, it is still difficult to solve this problem completely. Thus, we propose an SF-partition-based clustering and relaying (SFPCR) scheme to achieve enormous LD connectivity with fairness in IoT multihop LoRa networks. For the SF partition, the SFPCR scheme determines the suitable partitioning threshold point for bridging packet delivery success probability gaps between SF regions, namely, the lower SF zone (LSFZ) and the higher SF zone (HSFZ). To avoid long-distance transmissions to the GW, the HSFZ constructs a density-based subspace clustering that generates clusters of arbitrary shape for adjacent LDs and selects cluster headers by using a binary score representation. To support reliable data transmissions to the GW by multihop communications, the LSFZ offers a relay LD selection that ideally chooses the best relay LD to extend uplink transmissions from LDs in the HSFZ. Through simulations, we show that the proposed SFPCR scheme exhibits the highest success probability of 65.7%, followed by the FSRC scheme at 44.6%, the mesh scheme at 34.2%, and lastly the cluster-based scheme at 29.4%, and it conserves the energy of LDs compared with the existing schemes.

An Enhanced Localization Approach for Energy Conservation in Wireless Sensor Network with Q Deep Learning Algorithm

Wireless Sensor Networks (WSN) have distributed a collection of tiny sensor nodes deployed randomly in the given symmetry environment to sense natural phenomena. The sensed data are disseminated symmetrically to the control station using multi-hop communication. In WSN, the energy conservation during node coverage plays a major role in detecting node failure and providing efficient and symmetrical data transmission to the nodes of WSN. Using the cluster method and efficient localization techniques, the nodes are grouped and the precise location of the nodes is identified to establish the connection with the nearby nodes in the case of node failure. The location accuracy is achieved using the localization estimation of the anchor nodes and the nearest hop node distance estimation using the received signal strength measurement. The node optimization can be performed efficiently by the accurate estimation of the localization of the node. To optimize the node coverage and provide energy efficient and symmetrical localization among the nodes, in this paper, a cluster-based routing protocol and a novel bio-inspired algorithm, namely, Modified Bat for Node Optimization (MB−NO), to localize and optimize the unknown nodes along with the reinforcement-based Q learning algorithm is proposed with the motive of increasing the accuracy estimation between anchor nodes and the other neighbor nodes, with the objective function to optimize and improve the nodes’ coverage among the network’s nodes in order to increase the nodes’ localization accuracy. The distance metrics between the anchor nodes and other neighbor nodes have an estimated symmetry with three node positions, namely C-shape, S-shape and H-shape, using the Q learning algorithm. The proposed algorithm is implemented using the NS3 simulator. The simulation results show that the accuracy and precision of the proposed algorithm are achieved at 98% in the node coverage optimization with reduced Mean Localization Error (MLE) and computational process time compared with other bio-inspired algorithms, such as Artificial Bee Colony optimization and Genetic Algorithms.

An Hybrid Heuristic optimal relay selection strategy for energy efficient multi hop cooperative cellular communication

One of the major constraints for mobile relay networks is energy-efficient communication owing to the restricted battery power of user terminals. Among them, the production method is cooperative cellular networks that focus on enhancing the data rate, network reliability, and network system capacity and also improving the spectrum resources in the Fifth Generation (5 G) networks. Thus, recent research works investigate the selection of mobile relays in vehicular networks and also the relay selection in cooperative communication. Here, the mobile relay is selected by the base station (operator) for every mobile user for reducing the cost with improved data rates and reducing the total transmission power. The selection of relay is performed by considering the benefits or utilities offered to three players such as mobile relay, mobile user, and operator. Conventional relay node selection approaches face challenges regarding reduced network lifetime, delay, increased energy consumption, and collusion attacks. For next-generation wireless networks, both energy efficiency and capacity are vital. To cope with these problems, a new multi-objective derived energy efficient accurate selection of relay in multi-hop cooperative cellular communication in the vehicular network through a hybrid heuristic strategy is implemented. The conventional approaches are utilized for probability-based multi-hop broadcasting for low latency. On the other hand, the major demerits of cellular communication are developing an effective multi-hop communication strategy that generates hidden node problems, and also it decreases the speed of the vehicles and the lack of infrastructure in network topology. Thus, this paper aims to propose a hybrid optimization model to choose the lowest count of multi-hops among the source and destination for the cooperative cellular vehicular communication network. The major issue well thought-out here is accurately choosing the count of hops or relays for appropriate communication, which is carried out through the multi-objective function regarding link reliability, energy consumption, outage probability, mobility factor, and transmission delay of the system. The adoption of the new hybrid algorithm with the aid of the Best Fitness-derived Crow Tunicate Swarm Optimization (BF-CTSO) algorithm is designed as the major contribution for optimally selecting the multi-hops between source and destination in a cooperative cellular communication network. Numerical results show that the proposed energy-efficient cooperative communication system outperforms traditional methods.

Dynamic shielding to secure multi-hop communications in vehicular platoons

Vehicular platoons are among the most advanced driving assistance systems that may generate considerable fuel savings and increase traffic efficiency. However, communication between vehicles in a platoon is always vulnerable to eavesdropping due to the broadcast nature of wireless channels. To address this issue, we investigate security issues from the physical layer perspective for multi-hop vehicular platooning. The dynamic shielding secured transmission scheme is proposed to guarantee the confidential transmission of private information. Specifically, the neighboring vehicles can alternately act as friendly shielders, which transmit jamming signals to interfere with the eavesdroppers without knowing the channel state information, and thus the secrecy capacity would increase. The mathematical derivation of secrecy capacity is obtained for performance analysis. Meanwhile, the numerical results verify the properties, efficiency, and adaptability of the proposed scheme.

Hybrid 802.11p‐cellular architecture for NDN‐based VANET

SummaryVehicular network communications (VANET) face multiple challenges due to their intermittent connections and the rapid changes in their topologies. In recent years, several research efforts have explored the use of content‐centric approaches to alleviate some of these challenges. One of these promising network designs is Named Data Networking (NDN), which has become a valid solution to support VANET applications. However, in the NDN architecture, the main forwarding mechanism for the interest packets is flooding. This forwarding mechanism will result in excessive collisions, which will lead to the broadcast storm problem. In this paper, we propose VC‐NDN: a hybrid and hierarchical Named Data Networking architecture for VANETs. VC‐NDN improves content retrieval efficiency through an adapted NDN‐based communication model. VC‐NDN includes a new interest forwarding scheme to reduce packet collision in the network and an efficient mechanism to support push‐based traffic. Furthermore, to reduce communication costs, VC‐NDN uses two communication technologies in parallel, namely, IEEE 802.11p and cellular communications, while keeping the usage of the cellular network at a minimum level. Finally, to reduce the impact on vehicle mobility, VC‐NDN follows a hierarchical clustering architecture. Specifically, a density‐based clustering algorithm is designed to create and maintain stable clusters with multihop communication capability. Our performance study shows that VC‐NDN outperforms the basic VNDN solutions in terms of data retrieval delay and packet delivery ratio while minimizing the usage of the cellular network.

An Enhanced Energy Efficient Routing Protocol over Wireless Sensor Networks

Cluster-based hierarchical routing protocols play an essential role in decreasing the energy consumption of wireless sensor networks (WSNs). A low-energy adaptive clustering hierarchy (LEACH) has been proposed as an application-specific protocol architecture for WSNs. However, without considering the distribution of the cluster heads (CHs) in the rotation basis, the LEACH protocol will increase the energy consumption of the network. To improve the energy efficiency of the WSN, we propose a novel modified routing protocol in this paper. The newly proposed improved energy-efficient LEACH (IEE-LEACH) protocol considers the residual node energy and the average energy of the networks. To achieve satisfactory performance in terms of reducing the sensor energy consumption, the proposed IEE-LEACH accounts for the numbers of the optimal CHs and prohibits the nodes that are closer to the base station (BS) to join in the cluster formation. Furthermore, the proposed IEE-LEACH uses a new threshold for electing CHs among the sensor nodes, and employs single hop, multi-hop, and hybrid communications to further enhance the energy efficiency of the networks. The simulation results demonstrate that, compared with some existing routing protocols, the proposed protocol substantially reduces the energy consumption of WSNs.

A pseudonym-based certificateless privacy-preserving authentication scheme for VANETs

With the rapid development of wireless communication technology, Vehicular Ad-Hoc Networks (VANETs) is gradually becoming a key component for establishing core applications such as smart cities and the Intelligent Transportation System (ITS). However, due to the wireless multi-hop communication, VANETs is vulnerable to attacks. Therefore, the implementation of legitimacy authentication and conditional privacy preserving among entities in VANETs is a necessary prerequisite to ensure the security of VANETs. This paper proposes a secure and efficient conditional privacy preserving scheme for VANETs. Under the premise of guaranteeing the conditional privacy in VANETs, the anonymous authentication scheme is constructed by combining the pseudonym-based mechanism and the certificateless signature mechanism. Moreover, the scheme has great advantages in fast revocation of vehicles, and ensures that the pseudonyms cannot be linked before being traced. Security analysis proves that the proposed scheme is able to meet the privacy protection requirements in VANETs. In addition, the performance evaluation shows that the efficiency of the proposed scheme is significantly improved compared with the state-of-art schemes.

Denial-of-Service Attack Mitigation in Multi-hop 5G D2D Wireless Communication Networks Employing Double Auction Game

Denial-of-Service Attack Mitigation in Multi-hop 5G D2D Wireless Communication Networks Employing Double Auction Game

Energy-Efficient Edge Optimization Embedded System Using Graph Theory with 2-Tiered Security

The development of the Internet of Things (IoT) network has greatly benefited from the expansion of sensing technologies. These networks interconnect with wireless systems and collaborate with other devices using multi-hop communication. Besides data sensing, these devices also perform other operations such as compression, aggregation, and transmission. Recently, many solutions have been proposed to overcome the various research challenges of wireless sensor networks; however, energy efficiency with optimized intelligence is still a burning research problem that needs to be tackled. Thus, this paper presents an energy-efficient enabled edge optimization embedded system using graph theory for increasing performance in terms of network lifetime and scalability. First, minimum spanning trees are extracted using artificial intelligence techniques to improve the embedded system for response time and latency performance. Second, the extracted routes are provided with full protection against anonymous access in a two-tiered system. Third, the IoT systems collaborate with mobile sinks, and they need to be authenticated using lightweight techniques for the involvement in routing sensed information. Moreover, edge networks further provide the timely delivery of data to mobile sinks with less overhead on IoT devices. Finally, the proposed system is verified using simulations, revealing its significance to existing approaches.

Path selection and resource allocation for 5G multi-hop D2D networks

Multi-hop Device-to-Device (D2D) communication has emerged as one of the promising technologies to improve the network capacity of fifth generation (5G) networks. Existing research works focus on either increasing the throughput by streamlining radio-resource and power allocation approach or finding the best suitable path based on next-hop distance. However, there is very limited research work that covers the selection of the best path and resource allocation in multi-hop D2D communication. Therefore, in this paper, we proposed a path selection and resource allocation method. The proposed path selection method is based on the Q learning model in which the cumulative reward is calculated from source to destination. The proposed resource allocation method is divided into two-stage. In the first stage, a Max Mean Far (MMF) method is used to allocate the resource block in forming a multi-hop D2D. In the second stage, a hybrid combination of particle swarm optimization and gray wolf optimization (HPSOGWO) is applied over the first stage results. The HPSOGWO maximizes the system throughput by optimizing the power distribution of cellular and D2D users. In comparison to previously proposed approaches, this research process and findings ensure that system consistency and implementation are improved in all aspects.

Software-Defined Reconfigurable Intelligent Surfaces: From Theory to End-to-End Implementation

Programmable wireless environments (PWEs) utilize internetworked intelligent metasurfaces to transform wireless propagation into a software-controlled resource. In this article, the interplay is explored between the user devices, the metasurfaces, and the PWE control system from the theory to the end-to-end implementation. This article first discusses the metasurface hardware and software, covering the complete workflow from the user device initialization to its final service via the PWE. Furthermore, to be compatible with the 5G and 6G wireless systems, the software-defined networking (SDN) paradigm is extended to achieve scalable internetworking and central control in PWE deployments with multiple metasurfaces and multihop communication. Subsequently, the set of SDN foundations is exploited in order to abstract the physics behind PWEs and a theoretical framework is established to describe and manipulate them in an algorithmic form. This can lead to smart radio environments that are readily accessible from various engineering disciplines, facilitating their integration into existing networks, wireless systems, and applications. This article is concluded by outlining strategies for the optimal placement of metasurfaces within a PWE-controlled space, open challenges in PWE security, specialized SDN integration issues, and theoretical problems toward the graph-driven modeling of PWEs.

Privacy Preserving via Secure Summation in Distributed Kalman Filtering

Average consensus is a major operation in distributed Kalman filtering. It requires neighboring nodes to exchange state information with each other, which may result in undesirable private data leakage. Since distributed Kalman filtering requires that the estimate at each time instant is accurate, it brings more challenges to design privacy-preserving scheme for operation. In this article, we design a privacy-preserving scheme for distributed Kalman filtering without the loss of estimation performance, which is also suitable for average consensus or dynamic average consensus of multiagent systems. We first build a secure multihop communication based on an encryption scheme. We then calculate the sum of the states of neighboring nodes with secure summation, which ensures that the state update will not reveal the state of the node to its neighboring nodes. We employ different methods to calculate the sum of the states of neighboring nodes against noncollusive and collusive adversaries. For the noncollusive case, the privacy of the honest nodes is preserved. For the collusive case, if there are too many adversaries, the privacy of the honest nodes could be exposed when accurate distributed Kalman filtering is accomplished. Therefore, we measure the risk of the global system suffering privacy leakage as the privacy index and improve the ability of the system to defend the collusive adversaries by using a group-based method. Some numerical examples are provided to illustrate the effectiveness of the proposed schemes.

Performance analysis of multihop wireless systems with decode and forward relays over Fisher– Snedecor F fading channels

ABSTRACT By reducing the transmitting power at the base station and expanding the coverage range of wireless communication, cooperative communication has turned into a higher imperative. This article evaluates the outage probability, average symbol error rate (ASER) for coherent as well as noncoherent modulation pattern, ergodic capacity and throughput of a multihop communication technique over the Fisher–Snedecor F fading channels. The multihop transmission scheme utilises a source, a set of relays and the destination node. The intervening relays of the system are regenerative with decode and forward type. Each hop of the system undergoes Fisher–Snedecor F fading channels. The MGF-based approach is used to derive the ASER of the system. The outage probability and ASER performance upgrade with the advancement of fading parameter as well as shadowing parameter of the channel. The ergodic capacity decreases with the improvement in shadowing parameter and the number of hops. The throughput of the system rises in connection with the reduction of total hops. Simulations validate the correctness of the numerically appraised results.

CETS: Enabling Sustainable IoT with Cooperative Energy Transfer Schedule towards 6G Era.

The large scale of the Internet of Things necessitates using long-lasting physical layer devices for data collection. Deploying large numbers of Wi-Fi-enabled devices is expensive, so the Internet of Everything (IoE) is equipped with multiple communication modules to collect data where Wi-Fi is unavailable. However, because of their extended communication capabilities, IoE devices face energy limitations. As a result, IoE devices must be provided with the necessary energy resources. This paper introduces a novel multi-hop cooperation communication mechanism for Wireless Energy Transfer (WET) in the Wireless Powered-Internet of Everything (WP-IoE). IoE devices are outfitted here with various communication devices such as RF, Bluetooth, and Wi-Fi. This research proposes a two-phase energy transmission schedule to address the energy requirements. For data collection, the first phase provides a distributed tree-based data communication plan. The proposed model’s second phase used the reverse data collection protocol to implement wireless energy transmission. By combining these two phases, an optimized WET framework was created without unmanned aerial vehicles or robots. The experimental findings show that the proposed method in this research increases the average lifetime of the network and has a more significant charge latency and average charge throughput than other models.

Safe, Smooth, and Fair Rule-Based Cooperative Lane Change Control for Sudden Obstacle Avoidance on a Multi-Lane Road

When an unexpected obstacle occupies some of the lanes on a multi-lane highway, connected vehicles (CVs) may be able to avoid it cooperatively. For example, a CV that detects the obstacle first can immediately notify the following vehicles of the obstacle by using vehicle-to-vehicle (V2V) communication. In turn, the following vehicles can take action to avoid the obstacle smoothly using wide range behind the obstacle without sacrificing safety and ride comfort. In this study, we propose a method to realize safe, smooth, and fair wide-range cooperative lane changing, reacting to a sudden obstacle on the road. The proposed method is based on the authors’ previous work, which utilizes multi-hop communication to share the obstacle position and controls the inter-vehicular distance of vehicles away from the obstacle to assist in a smooth lane changing operation, while existing lane-changing methods for CVs focus on microscopic operation around the obstacle. Though the previous work treats only a two-lane road, the proposed method is extended to work on a three- or more lane road assuming only one lane is blocked. In the proposed scheme, each vehicle approaching the obstacle selects a lane to change to in accordance with the obstacle’s location and the vehicle density in each lane estimated from the beacon messages broadcast by each CV, thereby improving traffic fairness among all lanes without degrading safety or ride comfort. We confirmed the effectiveness of the proposed scheme on realizing fairness among lanes, safety, ride comfort, and traffic throughput through comprehensive simulations of a two-lane road and a three-lane road with various traffic scenarios.

OCHSA: Designing Energy-Efficient Lifetime-Aware Leisure Degree Adaptive Routing Protocol with Optimal Cluster Head Selection for 5G Communication Network Disaster Management

As an underlayment to cellular 5G communication network, device-to-device (D2D) communications will not only boost capacity utilization and power efficiency but also provide public health and public safety services. One of the most important requirements for these businesses is to have alternate access to cellular networks in the event that they are partially or completely disrupted as a result of a natural disaster. Despite limited communication coverage and bandwidth scarcity, the 3rd Generation Partnership Project (3GPP) must have developed a new device-to-device (D2D) communication method fundamental enhanced mobile that can strengthen spectral efficiencies besides allowing direct communication of gadgets in close propinquity devoid of transitory by elevated-node B (eNB). Unfortunately, enabling data transmission on a cellular connection offers a challenge in terms of two-way radio source administration, because D2D associates recycle cellular users’ uplink radio resources, which might create interference to D2D user equipment’s (DUE) receiving channels. In this study, we concentrate on optimal cluster head selection using the binary flower pollination optimization algorithm by designing an energy-efficient lifetime-aware leisure degree adaptive routing protocol named OptCH_L-LDAR. This topology is constructed with a multi-hop obliging communication system, instructed on the way to wrap an extensive remoteness connecting source and destination. The proposed OptCH_L-LDAR is compared with three state-of-art methods such as binary flower pollination (BFP) algorithm, time division multiple access (TDMA), and data-driven technique (DDT). As a result, the proposed OptCH_L-LDAR achieves 96% of energy efficiency, 89% of lifetime, 97% of outage probability, and 98% of spectral efficiency.