Energy Efficiency of Opportunistic Device-to-Device Relaying Under Lognormal Shadowing

Energy consumption is a major limitation of low power and mobile devices. Efficient transmission protocols are required to minimize an energy consumption of the mobile devices for ubiquitous connectivity in the next generation wireless networks. Opportunistic schemes select a single relay using the criteria of the best channel and achieve a near-optimal diversity performance in a cooperative wireless system. In this paper, we study the energy efficiency of the opportunistic schemes for device-to-device communication. In the opportunistic approach, an energy consumed by devices is minimized by selecting a single neighboring device as a relay using the criteria of minimum consumed energy in each transmission in the uplink of a wireless network. We derive analytical bounds and scaling laws on the expected energy consumption when the devices experience log-normal shadowing with respect to a base station considering both the transmission as well as circuit energy consumptions. We show that the protocol improves the energy efficiency of the network comparing to the direct transmission even if only a few devices are considered for relaying. We also demonstrate the effectiveness of the protocol by means of simulations in realistic scenarios of the wireless network.Comment: 30 pages, 8 figure

A Survey on Device-to-Device Communication in Cellular Networks

Device-to-Device (D2D) communication was initially proposed in cellular networks as a new paradigm to enhance network performance. The emergence of new applications such as content distribution and location-aware advertisement introduced new use-cases for D2D communications in cellular networks. The initial studies showed that D2D communication has advantages such as increased spectral efficiency and reduced communication delay. However, this communication mode introduces complications in terms of interference control overhead and protocols that are still open research problems. The feasibility of D2D communications in LTE-A is being studied by academia, industry, and the standardization bodies. To date, there are more than 100 papers available on D2D communications in cellular networks and, there is no survey on this field. In this article, we provide a taxonomy based on the D2D communicating spectrum and review the available literature extensively under the proposed taxonomy. Moreover, we provide new insights to the over-explored and under-explored areas which lead us to identify open research problems of D2D communication in cellular networks.Comment: 18 pages; 8 figures; Accepted for publication in IEEE Communications Surveys and Tutorial

TeamPhone: Networking Smartphones for Disaster Recovery

In this paper, we investigate how to network smartphones for providing communications in disaster recovery. By bridging the gaps among different kinds of wireless networks, we have designed and implemented a system called TeamPhone, which provides smartphones the capabilities of communications in disaster recovery. Specifically, TeamPhone consists of two components: a messaging system and a self-rescue system. The messaging system integrates cellular networking, ad-hoc networking and opportunistic networking seamlessly, and enables communications among rescue workers. The self-rescue system groups, schedules and positions the smartphones of trapped survivors. Such a group of smartphones can cooperatively wake up and send out emergency messages in an energy-efficient manner with their location and position information so as to assist rescue operations. We have implemented TeamPhone as a prototype application on the Android platform and deployed it on off-the-shelf smartphones. Experimental results demonstrate that TeamPhone can properly fulfill communication requirements and greatly facilitate rescue operations in disaster recovery

On Green Energy Powered Cognitive Radio Networks

Green energy powered cognitive radio (CR) network is capable of liberating the wireless access networks from spectral and energy constraints. The limitation of the spectrum is alleviated by exploiting cognitive networking in which wireless nodes sense and utilize the spare spectrum for data communications, while dependence on the traditional unsustainable energy is assuaged by adopting energy harvesting (EH) through which green energy can be harnessed to power wireless networks. Green energy powered CR increases the network availability and thus extends emerging network applications. Designing green CR networks is challenging. It requires not only the optimization of dynamic spectrum access but also the optimal utilization of green energy. This paper surveys the energy efficient cognitive radio techniques and the optimization of green energy powered wireless networks. Existing works on energy aware spectrum sensing, management, and sharing are investigated in detail. The state of the art of the energy efficient CR based wireless access network is discussed in various aspects such as relay and cooperative radio and small cells. Envisioning green energy as an important energy resource in the future, network performance highly depends on the dynamics of the available spectrum and green energy. As compared with the traditional energy source, the arrival rate of green energy, which highly depends on the environment of the energy harvesters, is rather random and intermittent. To optimize and adapt the usage of green energy according to the opportunistic spectrum availability, we discuss research challenges in designing cognitive radio networks which are powered by energy harvesters

Fundamental Green Tradeoffs: Progresses, Challenges, and Impacts on 5G Networks

With years of tremendous traffic and energy consumption growth, green radio has been valued not only for theoretical research interests but also for the operational expenditure reduction and the sustainable development of wireless communications. Fundamental green tradeoffs, served as an important framework for analysis, include four basic relationships: spectrum efficiency (SE) versus energy efficiency (EE), deployment efficiency (DE) versus energy efficiency (EE), delay (DL) versus power (PW), and bandwidth (BW) versus power (PW). In this paper, we first provide a comprehensive overview on the extensive on-going research efforts and categorize them based on the fundamental green tradeoffs. We will then focus on research progresses of 4G and 5G communications, such as orthogonal frequency division multiplexing (OFDM) and non-orthogonal aggregation (NOA), multiple input multiple output (MIMO), and heterogeneous networks (HetNets). We will also discuss potential challenges and impacts of fundamental green tradeoffs, to shed some light on the energy efficient research and design for future wireless networks.Comment: revised from IEEE Communications Surveys & Tutorial

Low-Rate Machine-Type Communication via Wireless Device-to-Device (D2D) Links

Wireless cellular networks feature two emerging technological trends. The first is the direct Device-to-Device (D2D) communications, which enables direct links between the wireless devices that reutilize the cellular spectrum and radio interface. The second is that of Machine-Type Communications (MTC), where the objective is to attach a large number of low-rate low-power devices, termed Machine-Type Devices (MTDs) to the cellular network. MTDs pose new challenges to the cellular network, one if which is that the low transmission power can lead to outage problems for the cell-edge devices. Another issue imminent to MTC is the \emph{massive access} that can lead to overload of the radio interface. In this paper we explore the opportunity opened by D2D links for supporting MTDs, since it can be desirable to carry the MTC traffic not through direct links to a Base Station, but through a nearby relay. MTC is modeled as a fixed-rate traffic with an outage requirement. We propose two network-assisted D2D schemes that enable the cooperation between MTDs and standard cellular devices, thereby meeting the MTC outage requirements while maximizing the rate of the broadband services for the other devices. The proposed schemes apply the principles Opportunistic Interference Cancellation and the Cognitive Radio's underlaying. We show through analysis and numerical results the gains of the proposed schemes.Comment: 12 Pages, 9 Figures, Submitted to JSAC "Device-to-Device Communications in Cellular Networks" on the 20th of May 201

Intelligent Wireless Communications Enabled by Cognitive Radio and Machine Learning

The ability to intelligently utilize resources to meet the need of growing diversity in services and user behavior marks the future of wireless communication systems. Intelligent wireless communications aims at enabling the system to perceive and assess the available resources, to autonomously learn to adapt to the perceived wireless environment, and to reconfigure its operating mode to maximize the utility of the available resources. The perception capability and reconfigurability are the essential features of cognitive radio while modern machine learning techniques project great potential in system adaptation. In this paper, we discuss the development of the cognitive radio technology and machine learning techniques and emphasize their roles in improving spectrum and energy utility of wireless communication systems. We describe the state-of-the-art of relevant techniques, covering spectrum sensing and access approaches and powerful machine learning algorithms that enable spectrum- and energy-efficient communications in dynamic wireless environments. We also present practical applications of these techniques and identify further research challenges in cognitive radio and machine learning as applied to the existing and future wireless communication systems

Network Slicing in Fog Radio Access Networks: Issues and Challenges

Network slicing has been advocated by both academia and industry as a cost-efficient way to enable operators to provide networks on an as-a-service basis and meet the wide range of use cases that the fifth generation wireless network will serve. The existing works on network slicing are mainly targeted at the partition of the core network, and the prospect of network slicing in radio access networks should be jointly exploited. To solve this challenge, an enhanced network slicing in fog radio access networks (F-RANs), termed as access slicing, is proposed. This article comprehensively presents a novel architecture and related key techniques for access slicing in F-RANs. The proposed hierarchical architecture of access slicing consists of centralized orchestration layer and slice instance layer, which makes the access slicing adaptively implement in an convenient way. Meanwhile, key techniques and their corresponding solutions, including the radio and cache resource management, as well as the social-aware slicing, are presented. Open issues in terms of standardization developments and field trials are identified

Compressive Rate Estimation with Applications to Device-to-Device Communications

We develop a framework that we call compressive rate estimation. We assume that the composite channel gain matrix (i.e. the matrix of all channel gains between all network nodes) is compressible which means it can be approximated by a sparse or low rank representation. We develop and study a novel sensing and reconstruction protocol for the estimation of achievable rates. We develop a sensing protocol that exploits the superposition principle of the wireless channel and enables the receiving nodes to obtain non-adaptive random measurements of columns of the composite channel matrix. The random measurements are fed back to a central controller that decodes the composite channel gain matrix (or parts of it) and estimates individual user rates. We analyze the rate loss for a linear and a non-linear decoder and find the scaling laws according to the number of non-adaptive measurements. In particular if we consider a system with $N$ nodes and assume that each column of the composite channel matrix is $k$ sparse, our findings can be summarized as follows. For a certain class of non-linear decoders we show that if the number of pilot signals $M$ scales like $M \sim k \log(N/k)$, then the rate loss compared to perfect channel state information remains bounded. For a certain class of linear decoders we show that the rate loss compared to perfect channel state information scales like $1/\sqrt{M}$

A Survey of Protocols and Standards for Internet of Things

The rapid growth in technology and internet connected devices has enabled Internet of Things (IoT) to be one of the important fields in computing. Standards, technologies and platforms targeting IoT ecosystem are being developed at a very fast pace. IoT enables things to communicate and coordinate decisions for many different types of applications including healthcare, home automation, disaster recovery, and industry automation. It is expected to expand to even more applications in the future. This paper surveys several standards by IEEE, IETF and ITU that enable technologies enabling the rapid growth of IoT. These standards include communications, routing, network and session layer protocols that are being developed to meet IoT requirements. The discussion also includes management and security protocols in addition to the current challenges in IoT which gives insights into the current research to solve such challenges.Comment: E-preprin