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Cognitive Radio (CR) promises an efficient utilization of radio spectrum resources by enabling dynamic spectrum access to overcome the spectrum scarcity problem. Cognitive Radio Sensor Networks (CRSNs) are one type of Wireless Sensor Networks (WSNs) equipped with CR capabilities. CRSN nodes need to operate energy-efficiently to extend network lifetime due to their limited battery capacity. In this paper, for the first time in literature, we formulate the problem of finding a common energy-efficient transmission range and transmission duration for all CRSN nodes and network deployment that would minimize the energy consumed per goodput per meter toward the sink in a greedy forwarding scenario. Results reveal non-trivial relations for energy-efficient CRSN transmission range and duration as a function of nine critical network parameters such as primary user activity levels. These relations provide valuable insights for detailed CRSN designs prior to deployment., 12 pages, 8 figures

The Internet of Things (IoT) is a key enabler for remote monitoring and control of any medium with wireless devices deployed in substantial numbers. However, these devices often lack the desired lifetimes due to their incompetent batteries. If the envisaged scale of the IoT is realized, replenishing millions of batteries will become impractical. To address this issue, joint utilization of two prominent technologies, energy harvesting (EH) and wireless power transfer (WPT), is explored in this paper. By coupling data from empirical measurements on EH profiles with Federal Communications Commission (FCC) regulations on indoor WPT, we propose and numerically evaluate design guidelines for energy-neutral wireless-powered networks, in which a source first extracts energy from its medium and then uses the collected energy to operate wireless devices via WPT. The initial findings reveal that the IoT devices in a 100m2 office building can be remotely energized by only three EH-enabled wireless power transmitting sources validating the proposed architecture.

Severe Acute Respiratory Syndrome-CoronaVirus 2 (SARS-CoV2) caused the ongoing pandemic. This pandemic devastated the world by killing more than a million people, as of October 2020. It is imperative to understand the transmission dynamics of SARS-CoV2 so that novel and interdisciplinary prevention, diagnostic, and therapeutic techniques could be developed. In this work, we model and analyze the transmission of SARS-CoV2 through the human respiratory tract from a molecular communication perspective. We consider that virus diffusion occurs in the mucus layer so that the shape of the tract does not have a significant effect on the transmission. Hence, this model reduces the inherent complexity of the human respiratory system. We further provide the impulse response of SARS-CoV2-ACE2 receptor binding event to determine the proportion of the virus population reaching different regions of the respiratory tract. Our findings confirm the results in the experimental literature on higher mucus flow rate causing virus migration to the lower respiratory tract. These results are especially important to understand the effect of SARS-CoV2 on the different human populations at different ages who have different mucus flow rates and ACE2 receptor concentrations in the different regions of the respiratory tract., Comment: IEEE Transactions on Molecular, Biological, and Multi-Scale Communications

The Internet of Things (IoT) is made up of interconnected devices for exchanging information through sensors and actuators. One of the main physical sensors to understand the environment beyond the visible world is a radar. Basically, radars have always been a military tool to investigate the environment. However, with the developing technology, radars have become more compact and affordable to use in a building, in a car, in a drone, or even in a wristwatch. In the near future, radar-equipped IoT platforms will start to appear increasingly. For each IoT platform, dual use of spectrum with dual aperture is required for sensing and communicating when using conventional approaches. Emissions from the radar and communication circuitries are the main causes of the increase in energy consumption for any radar sensing IoT device. Furthermore, an increasing number of radars cause congested spectrum, and RF convergence between radar and communication systems becomes more likely to present itself. In recent years, numerous research works have proposed using the single waveform for perceiving the environment and sending information. They are often called "joint radar-communication' (JRC) systems. As a result of the latest advancements in JRC system designs, radar sensing IoT platforms now can be transformed into an "Internet of Radars" (IoR). This article is an attempt to introduce a prospective research direction in order to develop the architectures necessary to make the IoR concept possible. In this article, we present a short survey of JRC technologies likely to be used on radar-sensing- capable IoT devices. Then possible application areas, challenges to enable JRC, and future research perspectives are proposed., NA

Communication among neurons, known as neuro-spike communication, is the most promising technique for realization of a bio-inspired nanoscale communication paradigm to achieve biocompatible nanonetworks. In neuro-spike communication, the information, encoded into spike trains, is communicated to various brain regions through neuronal network. An output neuron needs to receive signal from multiple input neurons to generate a spike. Hence, in this paper, we aim to quantify the information transmitted through the multiple-input single-output (MISO) neuro-spike communication channel by considering models for axonal propagation, synaptic transmission, and spike generation. Moreover, the spike generation and propagation in each neuron requires opening and closing of numerous ionic channels on the cell membrane, which consumes considerable amount of ATP molecules called metabolic energy. Thus, we evaluate how applying a constraint on available metabolic energy affects the maximum achievable mutual information of this system. To this aim, we derive a closed form equation for the sum rate of the MISO neuro-spike communication channel and analyze it under the metabolic cost constraints. Finally, we discuss the impacts of changes in number of pre-synaptic neurons on the achievable rate and quantify the tradeoff between maximum achievable sum rate and the consumed metabolic energy.

Using the advances in molecular communications (MCs), nanomachines as a group can undertake complex tasks. With the emergence of Internet of molecular things (IoMT), such nanomachine groups are now larger than ever. However, the minimal design of nanomachines makes cooperation difficult. In this paper, we investigate the performances of anarchic and cooperative transmitters in IoMT. We design an MC game in which nanomachines choose to cooperate or confront. We discuss the advantages and disadvantages of cooperation and state the possible transmitter personalities using game theoretic principles. Moreover, we focus on methods to ensure cooperation and we explore the optimal transmitter behavior if its partner rejects cooperation. Finally, we deduce that although ensuring cooperation may be done effectively with minimum hardware, anarchy is not necessarily a bad result. We also realize that in case a transmitter rejects cooperation, perpetual confrontation is not a good approach.

Understanding the fundamentals of communication among neurons, known as neuro-spike communication, leads to reach bio-inspired nanoscale communication paradigms. In this paper, we focus on a part of neuro-spike communication, known as axonal transmission, and propose a realistic model for it. The shape of the spike during axonal transmission varies according to previously applied stimulations to the neuron, and these variations affect the amount of information communicated between neurons. Hence, to reach an accurate model for neuro-spike communication, the memory of axon and its effect on the axonal transmission should be considered, which are not studied in the existing literature. In this paper, we extract the important factors on the memory of axon and define memory states based on these factors. We also describe the transition among these states and the properties of axonal transmission in each of them. Finally, we demonstrate that the proposed model can follow changes in the axonal functionality properly by simulating the proposed model and reporting the root mean square error between simulation results and experimental data.

Molecular communication (MC) is the most promising communication paradigm for nanonetwork realization since it is a natural phenomenon observed among living entities with nanoscale components. Since MC significantly differs from classical communication systems, it mandates re-investigation of information and communication theoretical fundamentals. The closest examples of MC architectures are present inside our own body. Therefore, in this paper, we investigate the existing literature on intrabody nanonetworks and different MC paradigms to establish and introduce the fundamentals of molecular information and communication science. We highlight future research directions and open issues that need to be addressed for revealing the fundamental limits of this science. Although the scope of this development encompasses wide range of applications, we particularly emphasize its significance for life sciences by introducing potential diagnosis and treatment techniques for diseases caused by dysfunction of intrabody nanonetworks., ERC project MINERVA; European Union project CIRCLE; Scientific and Technological Research Council of Turkey (TÜBİTAK)

Inspired by nature, molecular communications (MC), i.e., the use of molecules to encode, transmit, and receive information, stands as the most promising communication paradigm to realize the nanonetworks. Even though there has been extensive theoretical research toward nanoscale MC, there are no examples of implemented nanoscale MC networks. The main reason for this lies in the peculiarities of nanoscale physics, challenges in nanoscale fabrication, and highly stochastic nature of the biochemical domain of envisioned nanonetwork applications. This mandates developing novel device architectures and communication methods compatible with MC constraints. To that end, various transmitter and receiver designs for MC have been proposed in the literature together with numerable modulation, coding, and detection techniques. However, these works fall into domains of a very wide spectrum of disciplines, including, but not limited to, information and communication theory, quantum physics, materials science, nanofabrication, physiology, and synthetic biology. Therefore, we believe it is imperative for the progress of the field that an organized exposition of cumulative knowledge on the subject matter can be compiled. Thus, to fill this gap, in this comprehensive survey, we review the existing literature on transmitter and receiver architectures toward realizing MC among nanomaterial-based nanomachines and/or biological entities and provide a complete overview of modulation, coding, and detection techniques employed for MC. Moreover, we identify the most significant shortcomings and challenges in all these research areas and propose potential solutions to overcome some of them., This work was supported in part by the European Research Council (ERC) Projects MINERVA under Grant ERC-2013-CoG #616922 and MINERGRACE under Grant ERC-2017-PoC #780645.

Atmospheric ducts that are caused by the rapid decrease in the refractive index of the lower atmosphere can trap the propagating signals. The trapping effect of atmospheric ducts provides significant received power enhancements and enables signals to reach beyond-line-of-sight distances. Although wave propagation in atmospheric ducts are well studied, there is no work that provides fading and correlation analysis for atmospheric ducts. Therefore, the main motivation of this communication is to develop a large-scale path-loss model, estimate the distribution of fading, and analyze fading correlation for space and polarization diversity systems in the presence of surface ducts. Lastly, the achievable data rate results are presented to show the performance improvement with space and polarization diversity techniques., NA

Cognitive radio sensor networks (CRSNs) are event-based systems such that sensor nodes detect events and the event readings of the sensors are collaboratively conveyed in a multi-hop manner through vacant channels from event regions to a sink. Hence, the event-to-sink communication and the dynamic radio environment require a coordination scheme in CRSNs. In this paper, we propose a spectrum-aware clustering protocol to address the event-to-sink communication coordination issue in mobile CRSNs. Our clustering scheme consists of two phases. The first phase is the determination of nodes eligible for clustering, and the second phase is to form clusters among those nodes according to vacant spectrum bands. Clusters are temporary and they are not preserved after the end of events. Furthermore, we find average re-clustering probability, expected cluster coverage area, and find maximum event generation frequency for energy-efficient operation of our protocol. We study performance of our protocol in terms of control and data packet exchange, time steps required for clustering, connectivity of clusters, energy consumed for clustering, and re-clustering ratio due to the mobility. Performance comparison simulations show that our algorithm has better performance in terms of connectivity and energy consumption., Scientific and Technological Research Council of Turkey (TÜBİTAK)

Molecular devices, which consist of single or a few molecules, are envisioned to perform advanced tasks such as molecular information processing and collaborative sensing/actuating if they are operated in a cooperative manner. To connect these nanoscopic primitive devices with each other and with macroscale networks, and thus, to realize the internet of molecular devices, requires fundamentally different and novel approaches, other than the molecular or electromagnetic nanocommunications. Recently, we proposed and studied the use of Förster resonance energy transfer (FRET), which is a short-range nonradiative energy transfer process between fluorophores, as a high-rate and reliable wireless communication mechanism to connect fluorophore-based photoactive molecular devices. In this paper, we provide an in-depth architectural view of this new communication paradigm with a focus on its peculiarities, fundamental principles, and design requirements by comprehensively surveying the theoretical and experimental positions and ideas. We give an overview of networking opportunities offered by the intrinsic capabilities of fluorophores under the novel concept of Internet of Molecular Things. We present some prospective applications, theoretical modeling approaches, and experimental opportunities, and finally discuss the implementation challenges., European Research Council (ERC); Minerva; Scientific and Technological Research Council of Turkey (TÜBİTAK); Turkish National Academy of Sciences Distinguished Young Scientist Award Program (TÜBA-GEBİP); IBM Faculty Award

Cognitive radio (CR) is proposed to use the spectrum opportunistically. Spectrum opportunity (SOP) can be defined as the possibility of a spectrum-aware communication between a CR transmitter and a CR receiver. Successful spectrum-aware communication between the communicating CRs, which is utilization of SOP (USOP), depends on the SOP detection and the correct transmission of a packet. Spectrum sensing performance, physical channel, and network parameters affect the probability of USOP. In this letter, we characterize the probability of the USOP under different network topologies. The network topology is due to the relation between transmission ranges of licensed users and CRs. We numerically study this probability for different network parameters and topologies. We find that the characteristics of USOP highly depend on the network topology, CR sensing performance and licensed users' activities., Scientific and Technological Research Council of Turkey (TÜBİTAK)

Extensive use of amateur drones (ADrs) poses a threat to the public safety due to their possible misuse. Hence, surveillance drones (SDrs) are utilized to detect and eliminate potential threats. However, limited battery, and lack of efficient communication and networking solutions degrade the quality of surveillance. To this end, we conceptualize the Energy Neutral Internet of Drones (enIoD) to enable enhanced connectivity between drones by overcoming energy limitations for autonomous and continuous operation. Power provisioning with recharging stations is introduced by wireless power transfer to energize the drones. Renewable energy harvesting is utilized to realize energy neutrality, which is minimization of deficit in harvested and consumed energy in enIoD. Communication and networking architectures and protocols for realization of multi-dimensional objectives are presented. Finally, possible application areas are explained with a case study to show how enIoD operates.

CR enables dynamic spectrum access to utilize licensed spectrum when it is idle. CR technology is applied to wireless ad hoc and sensor networks to form CRAHNs and CRSNs, respectively. Clustering is an efficient topology management technique to regulate communication and allocate spectrum resources by CR capabilities of nodes in CRAHNs and CRSNs. In this article, we thoroughly investigate the benefits and functionalities of clustering such as topology, spectrum, and energy management in these networks. We also overview motivations for and challenges of clustering in CRAHNs and CRSNs. Existing clustering schemes are reviewed and compared. We conclude by revealing key considerations and possible solutions for spectrum-aware clustering in multi-channel CRAHNs and CRSNs., NA

Molecular Communication (MC) is a bioinspired communication technique that uses molecules as a method of information transfer among nanoscale devices. MC receiver is an essential component having profound impact on the communication system performance. However, the interaction of the receiver with information bearing molecules has been usually oversimplified in modeling the reception process and developing signal detection techniques. In this paper, we focus on the signal detection problem of MC receivers employing receptor molecules to infer the transmitted messages encoded into the concentration of molecules, i.e., ligands. Exploiting the observable characteristics of ligand-receptor binding reaction, we first introduce a Maximum Likelihood (ML) detection method based on instantaneous receptor occupation ratio, as aligned with the current MC literature. Then, we propose a novel ML detection technique, which exploits the amount of time the receptors stay unbound in an observation time window. A comprehensive analysis is carried out to compare the performance of the detectors in terms of bit error probability. In evaluating the detection performance, emphasis is given to the receptor saturation problem resulting from the accumulation of messenger molecules at the receiver as a consequence of intersymbol interference. The results reveal that detection based on receptor unbound time is quite reliable even in saturation, whereas the reliability of detection based on receptor occupation ratio substantially decreases as the receiver gets saturated. Finally, we also discuss the potential methods of implementing the detectors., European Research Council (ERC); European Union (European Union); H2020; MINERVA; CIRCLE

© 1997-2012 IEEE. Information transmission in the nervous system is performed through the propagation of spikes among neurons, which is done by vesicle release to chemical synapses. Understanding the fundamentals of this communication can lead to the implementation of bio-inspired nanoscale communication paradigms. In this letter, we utilize a realistic pool-based model for vesicle release and replenishment in hippocampal pyramidal neurons and evaluate the capacity of information transmission in this process by modeling it as a binary channel with memory. Then, we derive a recurrence relation for the number of available vesicles, which is used to find successful bit transmission probabilities and mutual information between input and output. Finally, we evaluate the spiking probability that maximizes mutual information and derive the capacity of the channel.

Wireless sensors equipped with cognitive radio, i.e., cognitive radio sensor networks (CRSN), can access the spectrum in an opportunistic manner and coexist with licensed users to mitigate the crowded spectrum problem and provide ubiquitous remote event monitoring and tracking for cyber-physical systems. In this paper, a novel transport layer protocol for CRSN, spectrum-aware energy-adaptive reliable transport protocol is presented to enable energy-adaptive collaborative event sensing in spectrum-scarce cyber-physical systems. To the best of our knowledge, this is the first attempt to specifically devise a reliable event transport scheme for CRSN., Scientific and Technological Research Council of Turkey (TÜBİTAK); Turkish National Academy of Sciences Distinguished Young Scientist Award Program

Troposcatter communication can be used as a communication medium for beyond-line-of-sight (BLOS) links. However, wave propagation in troposphere shows significant dependence on hydro-meteors: especially rain. Therefore, the main motivation of this paper is to develop a rain attenuation model for troposcatter communications, which can model nonuniform multiple rain cells for the first time. At the end, we present simulation results for the amount of rain loss and the distribution of maximum data rates under rain in troposcatter links., NA

Troposcatter is a promising candidate for beyond-line-of-sight (b-LoS) links because it can provide near-instantaneous point-to-point communication at distances of up to 300 km with high reliability. However, troposcatter communication is an underdeveloped research area. In this article, we review the channel modeling techniques for troposcatter. Most importantly, we analyze the coherence time and coherence bandwidth of troposcatter links for mobile receivers for the first time in the literature. In addition, we review the diversity techniques for troposcatter channels by outlining open research problems and possible application areas.

Atmospheric ducts, which are caused by the rapid decrease in the refractive index of the lower atmosphere, can trap the propagating signals. The trapping effects of the atmospheric ducts can be utilized as a communication medium for beyond-line-of-sight (b-LoS) links. Although the wave propagation and the refractivity estimation techniques for the atmospheric ducts are well studied, there is no work that provides a channel model for the atmospheric ducts. Therefore, we develop a large-scale path-loss model for the surface ducts based on the parabolic equation (PE) methods for the first time in the literature. In addition, we develop a ray-optics (RO) method to analyze the delay spread and angle-of-arrival (AOA) of the ducting channel with the surface ducts. Using the developed RO method, we derive an analytical expression for the effective trapping beamwidth of the transmitter to predict the ranges of the beamwidth that can be trapped by the surface ducts according to the refractivity and the channel parameters., NA

Spectrum sensing is an integral part of medium access control (MAC) in cognitive radio (CR) networks as its reliability determines the success of transmission. However, it is an energy-consuming operation that needs to be minimized for CR sensor networks (CRSNs) due to resource scarcity. In this paper, a cognitive adaptive MAC (CAMAC) protocol, which supports opportunistic transmission while addressing the issue of power limitation in CRSNs, is proposed. Energy conservation in CAMAC is achieved in three fronts: on-demand spectrum sensing, limiting the number of spectrum sensing nodes, and applying a duty cycle. Spectrum sensing is initiated on-demand when the nodes have data to transmit, and it also exploits a subset of spectrum sensing nodes to gather spectrum availability information for all the nodes. Furthermore, it defines an adaptive duty cycle for the CRSN nodes to periodically sleep and remains awake when data are available for transmission. Hence, CAMAC stands as an adaptive solution that employs the small number of spectrum sensing nodes with an adaptive sensing period yielding minimum energy consumption. Simulation results reveal the efficiency of CAMAC in terms of high throughput and less energy consumption, which is adaptive to primary users' traffic and duty cycle.

In nano-bio networks, multiple transmitter-receiver pairs will operate in the same medium. Both inter-symbol interference and multi-user interference can cause saturation at the receiver side, and this effect may cause an outage. Thus, we propose a tractable framework to calculate the theoretical operating points for fully absorbing receiver.

© 2002-2012 IEEE. Electric-field energy harvesting (EFEH) can be considered as an emerging and promising alternative for self-sustainable next-generation WSNs. Unlike conventional harvesting methods that rely on ambient variables, EFEH provides more reliable and durable operation as it is operable with any voltage-Applied conductive material. Therefore, it is better suited for advanced throughput and applications requiring a certain QoS. In this article, we introduce this newly emerging WSN paradigm, and focus on enabling EFEH technology for smart grid architectures, such as home, building, and near area networks, where the field intensity is relatively low. To this end, a practical methodology and a general use implementation framework have been developed for low-voltage applications by regarding compelling design issues and challenging source scarcity. The proposed double-layer harvester model is experimentally evaluated. Its performance in terms of implementation flexibility, sensor lifetime, and communication throughput is investigated. In addition, current challenges, open issues, and future research directions are discussed for the design of more enhanced EFEH wireless networks.

© 2016 IEEE. Network coding is mostly used to achieve the capacity of communication networks. In this paper, motivated by the nanoscale communications where the energy cost for the channel symbols is asymmetric due to the widely employed on-off keying modulation, we design energy-minimizing network codes. We develop the best mapping between the input and output symbols at the network coding node that minimizes the average codeword energy using Latin squares, which we call the minimum energy network code (MENC). We define the class of networks composed of coding nodes with N incoming and 1 outgoing symbols as in-N networks. First, we derive the condition on the network code to minimize the average energy in in-two networks and propose two linear MENCs. Later, we investigate the MENCs for in-N networks using the Latin hypercubes and propose a low-energy network code (LENC) to reduce the average energy with network coding. We compare MENC with the classical XOR and random network codes for in-two networks. The performance comparison between LENC and random network codes for in-N networks shows that the proposed network codes provide significant energy gains.

Near-surface wave propagation at microwave frequencies, especially 2 GHz and above, shows significant dependence on atmospheric ducts that are the layer in which rapid decrease in the refractive index occurs. The propagating signals in the atmospheric ducts are trapped between the ducting layer and the sea surface, so that the power of the propagating signals do not spread isotropically through the atmosphere. As a result, these signals have low path loss and can travel over the horizon. Since atmospheric ducts are nearly permanent in maritime and coastal environments, ducting layer communication is a promising method for b-LoS communications especially in naval communications. To this end, we overview the characteristics and the channel modeling approaches for ducting layer communications by outlining possible open research areas. In addition, we review the possible utilization of the ducting layer in network-centric operations to empower decision making for the b-LoS operations., NA

Virtual Multiple-Input Single-Output (MISO) is recently proposed to extend the benefits of transmitter space diversity to networks in which the deployment of antenna arrays on individual nodes is infeasible from a practical point of view. Ad-hoc and sensor networks are examples of these type of networks. In these scenarios, nodes equipped with single antenna can cooperatively transmit to emulate an antenna array. However, cooperative transmissions require knowledge of the channel state either at the transmitter side or the receiver side in order to achieve full performance gains. Several solutions are proposed in the literature under these assumptions, but at the expense of increased overhead and energy consumption. In this paper, the array gain at the receiver from the non-coherent combining of the signals from multiple transmitters is analyzed in statistical sense, under the assumption that the channel knowledge is unavailable. The transmitters are assumed to be randomly spread over a circular region. More specifically, exact or very accurate closed-form expressions for the expectation and variance of the array gain are obtained, and then a complete statistical distribution is postulated and validated by means of heuristic procedures, goodness-of-fit tests and specialized software. The results obtained in this paper can be especially useful for the implementation of two-tiered wide area sensor networks., Spanish Ministry of Science and Innovation

In the Molecular Communication (MC), molecules are utilized to encode, transmit, and receive information. Transmission of the information is achieved by means of diffusion of molecules and the information is recovered based on the molecule concentration variations at the receiver location. The MC is very prone to intersymbol interference (ISI) due to residual molecules emitted previously. Furthermore, the stochastic nature of the molecule movements adds noise to the MC. For the first time, we propose four methods for a receiver in the MC to recover the transmitted information distorted by both ISI and noise. We introduce sequence detection methods based on maximum a posteriori (MAP) and maximum likelihood (ML) criterions, a linear equalizer based on minimum mean-square error (MMSE) criterion, and a decision-feedback equalizer (DFE) which is a nonlinear equalizer. We present a channel estimator to estimate time varying MC channel at the receiver. The performances of the proposed methods based on bit error rates are evaluated. The sequence detection methods reveal the best performance at the expense of computational complexity. However, the MMSE equalizer has the lowest performance with the lowest computational complexity. The results show that using these methods significantly increases the information transmission rate in the MC., Scientific and Technological Research Council of Turkey (TÜBİTAK); Turkish National Academy of Sciences Distinguished Young Scientist Award Program (Turkish Academy of Sciences (TÜBA)-GEBIP); IBM through the IBM Faculty Award

We utilize the well known Additive Inverse Gaussian Noise (AIGN) communication channel to investigate the effect of diversity in diffusion-based molecular communication with drift, where the transmitter releases different types of molecules to the fluid medium by encoding the information onto the release time and type of molecules. The fluid channel imposes extra delay on the communication, and the receiver decodes the encoded information by solely utilizing the molecular arrival times. In this paper, simple receiver models based on maximum likelihood estimation (MLE) are investigated. Furthermore, upper and lower bounds on the capacity of AIGN communication channel with molecular diversity are derived., European Research Council; European Union; Horizon 2020; Minerva

This letter presents first results of a Terahertz (THz) band line-of-sight 2 x 2 multiple-input multiple-output (MIMO) channel. The system architecture is based on a subharmonic mixer that translates the measuring frequency of vector network analyzer in the range of 298-313 GHz. The system uses a virtual antenna array technique to characterize a MIMO channel. The antenna element spacing is derived from the principles of diffraction limited optics to establish parallel channels for higher system throughput and reliability. The MIMO channel measurements are then used in simulations to evaluate the performance of the communication system operating in THz band MIMO communication channel. Finally, we have shown the MIMO link in THz band operating at 7 Gb/s, with higher reliability, in comparison with the single channel operating at 5.55 Gb/s., Scientific and Technological Research Council of Turkey (TÜBİTAK)

Molecular communications, where molecules are used to encode, transmit, and receive information, are a promising means of enabling the coordination of nanoscale devices. The paradigm has been extensively studied from various aspects, including channel modeling and noise analysis. Comparatively little attention has been given to the physical design of molecular receiver and transmitter, envisioning biological synthetic cells with intrinsic molecular reception and transmission capabilities as the future nanomachines. However, this assumption leads to a discrepancy between the envisaged applications requiring complex communication interfaces and protocols, and the very limited computational capacities of the envisioned biological nanomachines. In this paper, we examine the feasibility of designing a molecular receiver, in a physical domain other than synthetic biology, meeting the basic requirements of nanonetwork applications. We first review the state-of-the-art biosensing approaches to determine whether they can inspire a receiver design. We reveal that the nanoscale field effect transistor-based electrical biosensor technology (bioFET) is particularly a useful starting point for designing a molecular receiver. Focusing on bioFET-based molecular receivers with a conceptual approach, we provide a guideline elaborating on their operation principles, performance metrics, and design parameters. We then provide a simple model for signal flow in silicon nanowire FET-based molecular receiver. Finally, we discuss the practical challenges of implementing the receiver and present the future research avenues from a communication theoretical perspective., European Research Council (ERC); Minerva

The emergence of wireless multimedia sensor networks (WMSNs) has made it possible to realize multimedia delivery on tiny sensing devices. The volume and characteristics of multimedia data is quite different from the data generated in WSNs that has raised the need to explore communication protocols for multimedia delivery in WMSNs. The existing studies focus on providing quality-of-service (QoS) to each individual source but they are not adaptive to create room for maximizing the number of sources. In this paper, we propose a novel cross-layer framework for QoS support in WMSNs. The objective of the proposed framework is to maximize the capacity of the deployed network to enhance the number of video sources given that the QoS constraint of each individual source is also preserved. This is achieved by implementing Wyner-Ziv lossy distributed source coding at the sensor node with variable group of pictures (GOP) size, exploiting multipath routing for real-time delivery and link adaptation to enhance the bandwidth under the given bit error rate. Hence, application requirements are mapped on joint operations of application, network, link and MAC layers to achieve the desired QoS. Simulation results reveal that the framework admits larger number of video sources under the satisfied distortion constraint.

Underwater physical medium is a challenging environment for communication using radio frequency (RF) or acoustic waves due to strong attenuation, delay, multi-path fading, power and cost limitations. Discovered a century ago, magneto-inductive (MI) communication technique stands as a strong alternative paradigm due to its independence of environmental impairments including multi-path fading, dynamic channels and high propagation delays experienced by acoustic waves. Furthermore, MI technique yields networking solutions exploiting low-cost, easily-deployable and flexible antenna structures, and the possibility of forming networks of magnetic waveguides defeating path loss. In this work, highly power efficient and fully connected underwater communication networks (UWCNs) composed of transceiver and relay induction coils are presented. Three dimensional (3D) UWCNs are analysed in terms of basic communication metrics, i.e, signal-to-noise ratio, bit-error rate, connectivity and communication bandwidth. The performance studies of realistic 3D networks covering hundreds of meters sea depths and a few km2 areas show that fully connected multi-coil networks with communication bandwidths extending from a few to tens of KHz are possible. Furthermore, the performance dependence on coil properties and network size is theoretically modelled. Results show that MI wireless communication is a promising alternative for UWCNs and future research challenges are pointed out.

A layered architecture incorporates the concept of minimum energy consumption for communication links and computer networks with multiple terminals, where emission-reduction approaches based on information theory are impractical., Türk Telekom; IBM Research University

Intermittently connected mobile cognitive radio ad hoc networks (IMCRNs) are promising wireless networks in which mobile unlicensed nodes use their temporarily available contacts and vacant licensed channels for end-to-end message delivery. In this paper, we propose biological foraging-inspired communication (BFC) algorithm for the energy-efficient and spectrum-aware communication requirements in IMCRNs. BFC is based on two profitability measures called relay selection profitability (RSP) and channel selection profitability (CSP). RSP and CSP provide an autonomous decision-making mechanism that does not need any a priori information on node mobility and spectrum availability patterns. This decision-making mechanism also leads to an optimization procedure to determine optimal relay and channel selection rules. Performance evaluations reveal that BFC enables each node to determine and regulate its transmission strategy to provide minimum energy consumption without sacrificing end-to-end delay performance. BFC also maximizes overall spectrum utilization in a way that any idle channel is always allocated by a node within a delay bound.

In this article, CAC to empower SUN inspiring from CR paradigm in wireless terrestrial communications is proposed. Spectrum scarcity in UAC due to the uniquely challenging underwater acoustic spectrum is discussed, and the need for spectrum-aware communication techniques is pointed out. We explore the capacity gain that can be achieved via CAC in SUN by simulation experiments and investigate the advantages and limitations of SUN along with its tradeoffs for DSA and OSA separately. Clearly, SUN can reach higher capacities than traditional fixed-spectrum approaches with the help of CAC capability. We expect that this article will provide better recognition for the capabilities of SUN and actuate further research efforts to explore this favorable area.

In this paper, based on the prey model in foraging theory, the BIO-inspired Cross-layer (BIOX) communication and coordination protocol is introduced for wireless sensor and actor networks (WSANs). BIOX permits each sensor node to autonomously determine its next-hop selection and channel access strategy using bio-inspired next-hop selection and channel access profitability measures. Based on these profitability measures, BIOX provides optimal performance in energy-efficient and reliable sensor-actor communication. Furthermore, using task allocation profitability measure, BIOX also guarantees stable allocation of available tasks in a way that each task is accomplished by an actor node within a bounded time delay. Performance evaluations reveal that BIOX significantly prolongs the network lifetime while providing highly reliable sensor-actor communication and effective task allocation for actor nodes.

Recently, wireless sensor networks have been considered as an opportunity to realize reliable and low-cost remote monitoring systems for smart grid. However, interference due to nonlinear electric power equipment and fading as a result of obstacles in various smart grid environments from generation to end-user sides make realization of reliable and energy-efficient communication a challenging task for WSNs in smart grid. In this article, spectrum-aware and cognitive sensor networks (SCSNs) are proposed to overcome spatio-temporally varying spectrum characteristics and harsh environmental conditions for WSN-based smart grid applications. Specifically, potential advantages, application areas, and protocol design principles of SCSN are introduced. The existing communication protocols and algorithms devised for dynamic spectrum management networks and WSNs are discussed along with the open research issues for the fulfillment of SCSNs. A case study is also presented to reveal the reliable transport performance in SCSNs for different smart grid environments. Lastly, different energy harvesting techniques for SCSN-based smart grid applications are reviewed. Here, our goal is to envision potentials of SCSNs for reliable and low-cost remote monitoring solutions for smart grid., European Union FP7 Marie Curie International Reintegration Grant (IRG); Scientific and Technological Research Council of Turkey (TÜBİTAK); Turkish National Academy of Sciences (Turkish Academy of Sciences (TÜBA)-GEBIP)

Cognitive radio (CR) technology helps mitigate wireless resource scarcity problem by dynamically changing frequency spectrum, power and modulation type. Opportunistic spectrum access increases the network capability and quality. Recently, CR applied to wireless sensor networks (WSNs) generated the paradigm of cognitive radio sensor networks (CRSNs) overcoming the challenges posed by event-driven traffic demands of WSNs. To realize advantages of CRSN, spectrum and power allocation, and routing must be jointly considered to maximize the information capacity, resource utilization and the lifetime. In this paper, power and rate adaptation problem is analyzed for a multi-hop CRSN in an information theoretical (IT) capacity maximization framework combined with energy adaptive (EA) mechanisms and utilization of sensor data information correlations (ICs). CRSN characteristics, i.e., fast data aggregation, bursty traffic and node failures, are considered. The capacity optimization problem is defined analytically and practical local schemes are presented showing the superiority of objective functions utilizing ICs and EA mechanisms in terms of the resulting maximum information rate at sink, i.e., R-max, lifetime, and energy utilization. Furthermore, dependence of performance on total bandwidth and various relay energy distributions is explored observing the logarithmic dependence of R-max on total bandwidth.

Using traditional sonar arrays may be difficult and impractical in some mission-critical scenarios, because they should be mounted on or towed by a ship or a submersible. Alternatively, underwater acoustic sensor networks (UW-ASNs) offer a promising solution approach. In this paper, a target-tracking algorithm for UW-ASNs, i.e., 3-D underwater target tracking (3DUT), is presented. The objective of 3DUT is to collaboratively accomplish accurate tracking of underwater targets with minimum energy expenditure. Based on the time of arrival of the echoes from the target after transmitting acoustic pulses from the sensors, the ranges of the nodes to the target are determined, and trilateration is used to obtain the location of the target. The location and the calculated velocity of the target are then exploited to achieve tracking. To realize energy-effective target tracking, 3DUT incorporates a new target-movement-based duty-cycle mechanism. To avoid rapid depletion of the energy resources of boundary nodes due to continuous surveillance, 3DUT employs an adaptive procedure to find, designate, and activate new boundary nodes. Performance evaluation shows that 3DUT is a promising alternative to the traditional sonar-based target-tracking approaches, particularly for on-demand surveillance applications.

Bio-inspired networking techniques have been investigated since more than a decade. Findings in this field have fostered new developments in networking, especially in the most challenging domains such as handling large-scale networks, their dynamic nature, resource constraints, heterogeneity, unattended operation, and robustness. Even though this new research area started with highly theoretical concepts, it can be seen that there is also practical impact. This article aims to give an overview to the general field of bio-inspired networking, introducing the key concepts and methodologies. Selected examples that outline the capabilities and the practical relevance are discussed in more detail. The presented examples outline the activities of a new community working on bio-inspired networking solutions, which is converging and becomes visible in term of the provided astonishingly efficient solutions., NA

Wireless sensor networks (WSN) have thus far been used for detection and tracking of static and mobile targets for mission critical surveillance applications. However, detection and tracking do not suffice for a complete and accurate target classification. In fact, surveillance target imaging yields the most valuable information. Current techniques mainly aim to provide images of static environment in a sensor network. Nevertheless, imaging of mobile targets requires networked and collaborative detection, tracking and imaging capabilities. With this regard, ultra-wideband (UWB) radar technology stands as a promising approach for networked target imaging due to its unique features such as having no line-of-sight (LoS) requirement. However, UWB wireless radar sensor network (WRSN) is yet to be developed for imaging of mobile targets. In this paper, an architecture and a new collaborative mobile target imaging (CMTI) algorithm for WRSN are presented. The objective is to efficiently obtain an accurate image of mobile targets based on the collaborative effort of deployed radar sensor nodes. CMTI enables detection, tracking and imaging of mobile targets as a complete WRSN solution. Performance evaluations reveal that CMTI yields high quality radar image of mobile targets inWRSN with very low communication overhead regardless of the target shape and velocity.

Recent developments in nanoscale electronics allow current wireless technologies to function in nanoscale environments. Especially due to their incredible electrical and electromagnetic properties, carbon nanotubes are promising physical phenomenon that are used for the realization of a nanoscale communication paradigm. This provides a very large set of new promising applications such as collaborative disease detection with communicating in-vivo nanosensor nodes and distributed chemical attack detection with a network of nanorobots. Hence, one of the most challenging subjects for such applications becomes the realization of nanoscale ad hoc networks. In this article, we define the concept of carbon nanotube-based nanoscale ad hoc networks for future nanotechnology applications. Carbon nanotube-based nanoscale Ad hoc NET-works (CANETs) can be perceived as the down-scaled version of traditional wireless ad hoc networks without downgrading its main functionalities. The objective of this work is to introduce this novel and interdisciplinary research field and highlight major barriers toward its realization.

Although many localization protocols have been proposed for terrestrial sensor networks in recent years, the unique characteristics of the underwater acoustic communication channel, such as high and variable propagation delay and the three dimensional volume of the environment make it necessary to design and develop new localization algorithms. In this paper, a localization algorithm called three-dimensional underwater localization (3DUL) is introduced. 3DUL achieves networkwide robust 3D localization by using a distributed and iterative algorithm. Most importantly, 3DUL exploits only three surface buoys for localization initially. The sensor nodes leverage the low speed of sound to accurately determine the inter-node distances. Performance evaluations show that 3DUL algorithm provides high accuracy in underwater localization, which does not degrade with network size.

The primary challenge in wireless sensor network deployment is the limited network lifetime due to finite-capacity batteries. Hence, the vast majority of research efforts thus far have focused on the development of energy-efficient communication and computing mechanisms for WSNs. In this article a fundamentally different approach and hence completely new WSN paradigm, the wireless passive sensor network, is introduced. The objective of the WPSN is to eliminate the limitation on system lifetime of the WSN. In a WPSN power is externally supplied to the sensor network node via an external RF source. Modulated backscattering is discussed as an alternative communication scheme for WPSNs. The feasibility is investigated along with the open research challenges for reliable communication and networking in WPSNs.

Wireless Sensor and Actor Networks (WSANs) are characterized by the collective effort of heterogenous nodes called sensors and actors. Sensor nodes collect information about the physical world, while actor nodes take action decisions and perform appropriate actions upon the environment. The collaborative operation of sensors and actors brings significant advantages over traditional sensing, including improved accuracy, larger coverage area and timely actions upon the sensed phenomena. However, to realize these potential gains, there is a need for an efficient transport layer protocol that can address the unique communication challenges introduced by the coexistence of sensors and actors. In this paper, a Real-Time and Reliable Transport (RT)2 protocol is presented for WSANs. The objective of the (RT)2 protocol is to reliably and collaboratively transport event features from the sensor field to the actor nodes with minimum energy dissipation and to timely react to sensor information with a right action. In this respect, the (RT)2 protocol simultaneously addresses congestion control and timely event transport reliability objectives in WSANs. To the best of our knowledge, this is the first research effort focusing on real-time and reliable transport protocol for WSANs. Performance evaluations via simulation experiments show that the (RT)2 protocol achieves high performance in terms of reliable event detection, communication latency and energy consumption in WSANs.