As quantum networking hardware remains costly and not yet widely accessible, simulation tools are essential for the design and evaluation of quantum network architectures and protocols. However, designing a scalable and computationally efficient quantum network simulator is intrinsically challenging: (i) quantum dynamics must be emulated on classical computing platforms while capturing the stateful and non-local nature of entanglement, a unique quantum resource without any classical networking analog; (ii) moreover, quantum networking is inherently hybrid, as protocol execution also fundamentally depends on classical signaling. This makes a tight and faithful co-simulation of quantum operations and classical message exchanges a core requirement. In this light, we present Q2NS , a modular and extensible quantum network simulator, built on top of ns-3, designed to seamlessly integrate quantum-network primitives with ns-3’s established classical protocol stack. Q2NS adopts a modular architecture that decouples protocol control logic from node- and channel-level operations, enabling rapid prototyping and adaptation across heterogeneous and evolving Quantum Internet scenarios. Q2NS natively supports multiple quantum state representations through a unified plug-in interface, allowing interchangeable state-vector, density-matrix, and stabilizer backends. We validate Q2NS through realistic use-case studies and comprehensive benchmarks, demonstrating superior computational efficiency over representative state-of-the-art alternatives, while preserving modeling flexibility. Finally, we provide a dedicated visualization tool that jointly captures physical and entanglement-enabled connectivity and supports entangled-state manipulations, facilitating an intuitive interpretation of entanglement dynamics and protocol behavior. Overall, Q2NS offers a flexible, open, and scalable simulation platform for advancing Quantum Internet research.

We introduce the concept of Quantum Ping (QPing) as a diagnostic primitive for future quantum networks, designed to assess whether two or more end nodes can establish practical quantum entanglement under given resource and time constraints, with controlled overhead and time-adaptive fidelity thresholds. Unlike classical ping, which probes network-layer connectivity through ICMP messages, our proposed quantum version is adapted to the unique features of quantum networks, where connectivity depends on the availability and quality of shared entanglement. We develop a formal framework for QPing and leverage tools such as sequential hypothesis testing to probe quantum connectivity. We present several strategies, including active strategies with path-based and segment-based variants, and resource-based strategies that utilize pre-shared entangled resources. We further provide a quantitative performance evaluation of these strategies, including diagnostic cost, latency, and feasibility under time-dependent decoherence. QPing can serve as a flexible diagnostic building block for quantum networks, designed to operate alongside fundamental network operations and to accommodate different architectural assumptions and protocol design approaches.

The key objective of the Quantum Internet is the distribution and manipulation of entanglement to enable unprecedented applications. This requires a radical departure from classical Internet design principles, such as the end-to-end argument, due to the inherently stateful and non-local nature of entanglement, which demands coordinated in-network operations and persistent state awareness. To this end, we propose a novel hierarchical Quantum Internet architecture centered on the concept ofEntanglement-Defined Controller(EDC). This architectural design constitutes the foundational layer, by enabling a clear separation between control and data planes. While necessary, this separation is insufficient to manage entanglement resources, requiring aquantum-native control plane. Consequently, we propose aquantum addressing schemethat embeds quantumness directly into node identifiers, allowing the network to natively track and manipulate entanglement as a dynamic resource. Built upon these two interdependent pillars – EDC-based architecture and quantum addressing – we design aquantum-native routing protocolthat achieves scalability through compact routing tables, by efficiently operating over entanglement-defined topologies. Finally, we design aquantum address splittingfunctionality based on Schrödinger’s oracles that generalizes classical match-and-forward logic to the quantum domain. Collectively, these contributions demonstrate, for the first time, the fundamental advantages of quantum-by-design network control for enabling scalable quantum networking.

In the Quantum Internet, multipartite entanglement enables a rich and dynamic overlay topology, referred to as artificial topology, upon the physical one, that can be exploited for communication purposes. In fact, the ability to extractn-qubits GHZ states and EPR pairs from the original multipartite entangled state constitutes the resource primitives for end-to-end and on-demand quantum communications. Thus, in this paper, we theoretically determine upper and lower bounds for the number of extractablen-qubits GHZ states and EPR pairs involving nodes remote in the artificial topology, as well as the achievable sizenof remote GHZ states. The theoretical analysis is then complemented by the proposal of a novel algorithm, which provides in polynomial-time a heuristic solution to the above problem. This is remarkable, since the theoretical problem is NP-complete. The performance analysis demonstrates the proposed algorithm is able to effectively manipulate the original and arbitrary graph state for extracting entanglement resources across remote nodes.

Superconducting and photonic technologies are envisioned to play a key role in the Quantum Internet. However the hybridization of these technologies requires functional quantum transducers for converting superconducting qubits, exploited in quantum computation, into “flying” qubits, able to propagate through the network (and vice-versa). In this paper, quantum transduction is theoretically investigated for a key functionality of the Quantum Internet, namely, multipartite entanglement distribution. Different communication models for quantum transduction are provided, in order to make the entanglement distribution possible. The proposed models departs from the large heterogeneity of hardware solutions available in literature, abstracting from the particulars of the specific solutions with a communication engineering perspective. Then, a performance analysis of the proposed models is conducted through key communication metrics, such as quantum capacity and entanglement generation probability. The analysis reveals that – although the considered communication metrics depend on transduction hardware parameters for all the proposed models – the particulars of the considered transduction paradigm play a relevant role in the overall entanglement distribution performance.

Nowadays, quantum computing has reached the engineering phase, with fully-functional quantum processors integrating hundreds of noisy qubits. Yet – to fully unveil the potential of quantum computing out of the labs into the business reality – the challenge ahead is to substantially scale the qubit number, reaching orders of magnitude exceeding thousands of fault-tolerant qubits. To this aim, the distributed quantum computing paradigm is recognized as the key solution for scaling the number of qubits. Indeed, accordingly to such a paradigm, multiple small-to-moderate-scale quantum processors communicate and cooperate for executing computational tasks exceeding the computational power of single processing devices. The aim of this survey is to provide the reader with an overview about the main challenges and open problems arising with distributed quantum computing from a computer and communications engineering perspective. Furthermore, this survey provides an easy access and guide towards the relevant literature and the prominent results in the field.

The Quantum Internet is envisioned as a global network, interconnecting heterogeneous quantum networks, able to transmit quantum information (qubits, qudits, or continuous variables) and to distribute entangled quantum states with no classical equivalent, by exploiting quantum links in synergy with classical links. The Quantum Internet is disruptive, since it is capable of supporting functionalities with no direct counterpart in classical networks, such as advanced quantum cryptographic services, blind quantum computing, and distributed quantum computing characterized by exponential increases in computing power and new forms of communication. These functionalities have the potential to fundamentally change the world in ways we cannot imagine yet.

Multipartite entanglement plays a crucial role for the design of the Quantum Internet, due to its peculiarities with no classical counterpart. Yet, for entanglement-based quantum networks, a key open issue is constituted by the lack of an effectiveentanglement access control(EAC) strategy for properly handling and coordinating the quantum nodes in accessing the entangled resource. In this paper, we design aquantum-genuineentanglement access control (EAC) to solve the contention problem arising in accessing a multipartite entangled resource. The proposed quantum-genuine EAC is able to: i) fairly select a subset of nodes granted with the access to the contended resource; ii) preserve the privacy and anonymity of the identities of the selected nodes; iii) avoid to delegate the signaling arising with entanglement access control to the classical network. We also conduct a theoretical analysis of noise effects on the proposed EAC. This theoretical analysis is able to catch the complex noise effects on the EAC through meaningful parameters.

Multipartite entanglement distribution is a key functionality of the Quantum Internet. However, quantum entanglement is very fragile, easily degraded by decoherence, which strictly constraints the time horizon within the distribution has to be completed. This, coupled with the quantum noise irremediably impinging on the channels utilized for entanglement distribution, may imply the need to attempt the distribution process multiple times before the targeted network nodes successfully share the desired entangled state. And there is no guarantee that this is accomplished within the time horizon dictated by the coherence times. As a consequence, in noisy scenarios requiring multiple distribution attempts, it may be convenient to stop the distribution process early. In this paper, we take steps in the direction of knowing when to stop the entanglement distribution by developing a theoretical framework, able to capture the quantum noise effects. Specifically, we first prove that the entanglement distribution process can be modeled as a Markov decision process. Then, we prove that the optimal decision policy exhibits attractive features, which we exploit to reduce the computational complexity. The developed framework provides quantum network designers with flexible tools to optimally engineer the design parameters of the entanglement distribution process.

Multipartite entanglement plays a crucial role in the Quantum Internet design, due to its potentiality of significantly increasing the network performance. In this paper, we identify the four key network functionalities for managing multipartite entanglement among remote nodes. And we discuss each functionality by considering - as case study - a specific multipartite state, which exhibits an attractive computing feature. Specifically, the designed state allows an arbitrary entangled node to calculate - in a distributed way - the sum of a set of values arbitrarily selected by the remaining entangled nodes.

A crucial step towards the 6th generation (6G) of networks would be a shift in communication paradigm beyond the limits of Shannon’s theory. In both classical and quantum Shannon’s information theory, communication channels are generally assumed to combine throughclassical trajectories, so that the associated network path traversed by the information carrier is well-defined. Counter-intuitively, quantum mechanics enables a quantum information carrier to propagate through aquantum path, i.e., through a path such that the causal order of the constituting communications channels becomes indefinite. Quantum paths exhibit astonishing features, such as providing non-null capacity even when no information can be sent through any classical path. In this paper, we study the quantum capacity achievable via a quantum path and establish upper and the lower bounds for it. Our findings reveal the substantial advantage achievable with a quantum path over any classical placements of communications channels in terms of ultimate achievable communication rates. Furthermore, we identify the region where a quantum path incontrovertibly outperforms the amount of transmissible information beyond the limits of conventional quantum Shannon’s theory, and we quantify this advantage over classical paths through a conservative estimate.

Practical distributed quantum computing requires the development of efficient compilers, able to make quantum circuits compatible with some given hardware constraints. This problem is known to be tough, even for local computing. Here, we address it on distributed architectures. As generally assumed in this scenario, telegates represent the fundamental remote (inter-processor) operations. Each telegate consists of several tasks: (i) entanglement generation and distribution, (ii) local operations, and (iii) classical communications. Entanglement generations and distribution is an expensive resource, as it is time-consuming. To mitigate its impact, we model an optimization problem that combines running-time minimization with the usage of distributed entangled states. Specifically, we formulated the distributed compilation problem as a dynamic network flow. To enhance the solution space, we extend the formulation, by introducing a predicate that manipulates the circuit given in input and parallelizes telegate tasks. To evaluate our framework, we split the problem into three sub-problems, and solve it by means of an approximation routine. Experiments demonstrate that the run-time is resistant to the problem size scaling. Moreover, we apply the proposed algorithm to compile circuits under different topologies, showing that topologies with a higher ratio between edges and nodes give rise to shallower circuits.

To realize the Quantum Internet, quantum communications require pre-shared entanglement among quantum nodes. However, both the generation and the distribution of the maximally-entangled quantum states are inherently contaminated by quantum decoherence. Conventionally, the quantum decoherence is mitigated by performing the consecutive steps of quantum entanglement distillation followed by quantum teleportation. However, this conventional approach imposes a long delay. To circumvent this impediment, we propose a novel quantum communication scheme relying on realistic noisy pre-shared entanglement, which eliminates the sequential steps imposing delay in the standard approach. More precisely, our proposed scheme can be viewed as a direct quantum communication scheme capable of improving the quantum bit error ratio (QBER) of the logical qubits despite relying on realistic noisy pre-shared entanglement. Our performance analysis shows that the proposed scheme offers competitive QBER, yield, and goodput compared to the existing state-of-the-art quantum communication schemes, despite requiring fewer quantum gates.

The unique and often-weird properties of quantum mechanics allow an information carrier to propagate through multiple trajectories of quantum channels simultaneously. This ultimately leads us to quantum trajectories with an indefinite causal order of quantum channels. It has been shown that indefinite causal order enables the violation ofbottleneck capacity, which bounds the amount of the transferable classical and quantum information through a classical trajectory with a well-defined causal order of quantum channels. In this treatise, we investigate this beneficial property in the realm of both entanglement-assisted classical and quantum communications. To this aim, we derive closed-form capacity expressions of entanglement-assisted classical and quantum communication for arbitrary quantum Pauli channels over classical and quantum trajectories. We show that by exploiting the indefinite causal order of quantum channels, we obtain capacity gains over classical trajectory as well as the violation of bottleneck capacity for various practical scenarios. Furthermore, we determine the operating region where entanglement-assisted communication over quantum trajectory obtains capacity gain against classical trajectory and where the entanglement-assisted communication over quantum trajectory violates the bottleneck capacity.

The quantum switch has been witnessing growing attention in the last years due to its advantage in several quantum technologies applications. In particular, it has been proven that the quantum switch can significantly improve the communication rates beyond the limits of conventional quantum Shannon theory. In this paper, we theoretically prove that the quantum switch can be interpreted as a particular instance of the Environment-assisted quantum communication paradigm. The developed analysis is crucial to better understand the limitations of the quantum switch. Furthermore, the analysis is key to shed the light on control strategies within the Environment-assisted communication paradigm.

Counter-intuitively, quantum mechanics enables quantum particles to propagate simultaneously among multiple space-time trajectories. Hence, a quantum information carrier can travel through different communication channels in a quantum superposition of different orders, so that the relative causal order of the communication channels becomes indefinite. This is realized by utilizing a quantum device known as quantum switch. In this paper, we investigate, from a communications engineering perspective, the use of the quantum switch within the quantum teleportation process, one of the key functionalities of the Quantum Internet. Specifically, a theoretical analysis is conducted to quantify the performance gain that can be achieved by employing a quantum switch for the entanglement distribution process within the quantum teleportation, with respect to the case of absence of the quantum switch. The analysis reveals that, by utilizing the quantum switch, the quantum teleportation is heralded as a noiseless communication process with a probability that, remarkably and counter-intuitively, increases with the noise levels affecting the communication channels considered in the indefinite-order combination.

Quantum Teleportation is the key communication functionality of the Quantum Internet, allowing the “transmission” of qubits without the physical transfer of the particle storing the qubit. Quantum teleportation is facilitated by the action of quantum entanglement, a somewhat counter-intuitive physical phenomenon with no direct counterpart in the classical word. As a consequence, the very concept of the classical communication system model has to be redesigned to account for the peculiarities of quantum teleportation. This re-design is a crucial prerequisite for constructing any effective quantum communication protocol. The aim of this manuscript is to shed light on this key concept, with the objective of allowing the reader: i) to appreciate the fundamental differences between the transmission of classical information versus the teleportation of quantum information; ii) to understand the communications functionalities underlying quantum teleportation, and to grasp the challenges in the design and practical employment of these functionalities; iii) to acknowledge that quantum information is subject to the deleterious effects of a noise process termed as quantum decoherence. This imperfection has no direct counterpart in the classical world; iv) to recognize how to contribute to the design and employment of the Quantum Internet.

After decades of pure science phase, the research on quantum technologies is finally reaching the engineering phase, getting out of the labs into business reality. Quantum technologies relies on quantum bits, aka qubits, which are the equivalent of classical bits used in classical information processing. Similarly to bits, the information stored in qubits can be corrupted by classical noise. Differently from bits, qubits are also vulnerable to quantum noise, a type of noise with no counterpart in the classical world. Hence, it becomes crucial to understand, from an engineering perspective, how the quantum noise corrupts the information stored within a qubit. To this aim, in this invited paper, we overview the effects of the quantum noise on an arbitrary qubit from a signal-processing perspective.

Due to the worldwide ongoing pressure to massively exploit the Sub-6 GHz spectrum for the deployment of independently-operated and heterogeneous networks, innovative solutions for network coexistence are deeply required. Hence, in this paper, we design a self-organizing strategy with the aim of minimizing the coexistence interference among heterogeneous networks sharing the Sub-6 GHz spectrum. The design is performed under the constraints of promoting selfless network utilization and avoiding any direct communication among the heterogeneous networks. For this, we develop an analytical framework, grounded on the nest-site selection behavior observed in honeybee swarms, to model the coexistence problem among multiple heterogeneous networks. Specifically, first, different heterogeneous networks are mapped into different populations and the allocation of a Sub-6 GHz band to a network is mapped into the population commitment. Then, the evolution of the commitment process is described through a multi-dimensional differential system. We analytically study the stability of such a system at the equilibrium, and we derive the conditions that assure the optimal allocation of the available Sub-6 GHz bands among the different heterogeneous networks. Finally, the proposed strategy is validated through an extensive performance evaluation.

One of the main challenges for continued wireless capacity growth is the difficulty in exploiting the multicast nature of the wireless medium: wireless end points rarely experience the same channel conditions or access the same content at the same time. In this paper, we present and analyze a novel wireless video delivery paradigm based on the combined use of channel-aware caching and coded multicasting that allows simultaneously serving multiple cache-enabled access points that may be requesting different content and experiencing different channel conditions. To this end, we reformulate the caching-aided coded multicast problem as a joint source-channel coding problem and design an achievable scheme that preserves the cache-enabled multiplicative throughput gains of the error-free scenario, by guaranteeing per-receiver (access point) rates unaffected by the presence of receivers with worse channel conditions.

Very recently, regulatory bodies worldwide started to approve the opportunistic access of unlicensed networks to the TVWS spectrum. Hence, in the near future, multiple heterogeneous and independently-operated unlicensed networks will coexist within the same geographical area over shared TVWS. Nevertheless, the coexistence among heterogeneous unlicensed networks over TVWS represents an open problem, and innovative solutions for handling the coexistence interference are needed to fully unleash the TVWS potentials. Hence, in this paper, we design a coexistence strategy for TVWS scenarios with the following attractive features: i) fully distributed, i.e., it avoids the need of centralized interference management; ii) over-the-air communications free, i.e., it avoids the need of direct communications among the heterogeneous networks; iii) adaptive to the time- and space-dynamics of the coexistence interference; iv) selfless, i.e., it allows a fair TVWS spectrum sharing by accounting for the communication demands of each unlicensed network. These attractive features are obtained by designing a coexistence strategy based on a system of multi-dimensional ordinary differential equations, and by incorporating the tradeoff between selfish bandwidth maximization and fair spectrum allocation within the system dynamics. Performance evaluation is conducted through numerical simulations, and the results confirm the attractive features of the proposed coexistence strategy.

Intrabody nanonetworks for nervous system monitoring are envisioned as a key application of the Internet of Nano-Things (IoNT) paradigm, with the aim of developing radically new medical diagnosis and treatment techniques. Indeed, very recently, bionic devices have been implanted inside a living human brain as innovative treatment for drug-resistant epilepsy. In this context, this paper proposes a systems-theoretic communication model to capture the actual behavior of biological neurons. Specifically, biological neurons exhibit physical extension due to their projections called dendrites, which propagate the electrochemical stimulation received via synapses to the soma. Experimental evidences show that the dendrites exhibit two main features: 1) the compartmentalization at the level of the dendritic branches of the neuronal processes and 2) the location-dependent preference for different frequencies. Stemming from these experimental evidences, we propose to model the dendritic tree as a spatiotemporal filter bank, where each filter models the behavior in both space and time of a dendritic branch. Each filter is fully characterized along with the overall neuronal response. Furthermore, sufficient conditions on the incoming stimulus for inducing a null-neuronal response are derived. The conducted theoretical analysis shows that: 1) the neuronal information is encoded in the stimulus temporal pattern, i.e., it is possible to select the neuron to affect by changing the stimulus frequency content; in this sense, the communication among neurons is frequency-selective and 2) the spatial distribution of the dendrites affects the neuronal response; in this sense, the communication among neurons is spatial-selective. The theoretical analysis is validated through a real neuron morphology.

Future Internet usage will be dominated by the consumption of a rich variety of online multimedia services accessed from an exponentially growing number of multimedia capable mobile devices. As such, future Internet designs will be challenged to provide solutions that can deliver bandwidth-intensive delay-sensitive on-demand video-based services over increasingly crowded and bandwidth-limited wireless access networks. One of the main reasons for the bandwidth stress facing wireless network operators is the difficulty to exploit the multicast nature of the wireless medium when wireless users or access points rarely experience the same channel conditions or access the same content at the same time. In this paper, we present and analyze a novel wireless video delivery paradigm based on the combined use of channel-aware caching and coded multicasting that allows simultaneously serving multiple cache-enabled receivers that may be requesting different content and experiencing different channel conditions. To this end, we reformulate the caching-aided coded multicast problem as a joint source-channel coding problem and design an achievable scheme that preserves the cache-enabled multiplicative throughput gains of the error-free scenario, by guaranteeing per-receiver rates unaffected by the presence of receivers with worse channel conditions.

Experimental evidences show that: 1) the release sites from a single axon have variable release probabilities, even when the axon contacts the same postsynaptic neuron; 2) this variability in the release probability implies a compartmentalization at the level of the presynaptic terminals of the neuronal processing; 3) the specificity of the presynaptic terminal processing is driven by and reflects the complex biophysical mechanisms activated at the axon terminals when a spike is fired in response to a stimulus. Stemming from these experimental evidences, we propose a communication engineering model for capturing the behavior of biological neurons. Specifically, by adopting a stochastic approach, the presynaptic terminals are modeled as a dynamic array of transmitters, where each transmitter models the processing specificity of a presynaptic terminal. In particular, we first show that the unique and specific processing of a presynaptic terminal can be reconducted to the cascade of a frequency selector and an amplitude modulator. Then, we characterize the propagation of the presynaptic-filtered signal through the synaptic cleft, and we derive the delay along with the channel attenuation as a function of the distance between the communicating neurons. Finally, the theoretical analysis is validated through numerical simulation.

In TV White Space, the unlicensed users are required to periodically access a database to acquire information on the spectrum usage of the licensed users. In addition, the unlicensed users can access the database on-demand, whenever they believe convenient, to update the spectrum availability information. In this paper, we design the optimal database access strategy, i.e., the strategy allowing the unlicensed users to jointly: (1) maximize the expected overall communication opportunities through on-demand accesses; and (2) respect the regulatory specifications. To this aim, we develop a stochastic analytical framework that allows us to account for: (1) the PU activity dynamics; (2) the quality dynamics among the different channels; and (3) the overhead induced by the database access. Specifically, at first, we prove that the database access problem can be modeled as a Markov decision process, and we show that it cannot be solved through brute-force search. Then, we prove that the optimal strategy exhibits a threshold structure, and we exploit this threshold property to design an algorithm able to efficiently compute the optimal strategy. The analytical results are finally validated through simulations.

To fully unleash the potentials of the cognitive radio (CR) paradigm, new challenges must be addressed. Specifically, as regards the network layer, the problem of the route priority, i.e., the problem of prioritizing the routes for the CR packet transmission, is crucial, since the communication opportunities provided by a route are deeply affected by the primary-user (PU) activity. Furthermore, whenever the CR network layer exploits proactively acquired information on the PU activity, update packets need to be exchanged among the CR users, inducing so a route overhead independently of the adopted routing protocol. Hence, in this paper, we analytically derive the optimal route priority rule, i.e., the route priority rule maximizing the achievable capacity, by jointly accounting for the PU activity and the route overhead. To this aim, at first, we formulate the optimal route priority problem, and we prove that its computational complexity through exhaustive search is exponential. Then, we provide the closed-form expressions of the achievable capacity. Stemming from these expressions, we derive the optimal route priority, and we design a computational-efficient search algorithm. All the theoretical results are derived by adopting two routing strategies and two PU activity models.

A key issue of the spectrum sensing functionality in Cognitive Radio (CR) networks is the ability of tuning the sensing time parameters, i.e., the sensing time and the transmission time, according to the Primary User (PU) network dynamics. In fact, these parameters influence both the spectrum sensing efficiency and the PU interference avoidance. This issue becomes even more challenging in presence of PU mobility. In this paper, an optimal spectrum sensing design for mobile PU scenarios is proposed with the aim to achieve the following important features: i) to determine the optimal mobility-aware transmission time, i.e., the transmission time value that jointly maximizes the spectrum sensing efficiency and satisfies the PU interference constraint; ii) to determine the optimal mobility-aware sensing time threshold, i.e., the maximum sensing time value assuring efficient spectrum sensing. First, closed-form expressions of both the optimal transmission time and the optimal sensing time threshold are analytically derived for a general PU mobility model. Then, the derived expressions are specialized for two widely adopted mobility models, i.e., the Random Walk mobility Model with reflection and the Random Way-Point mobility Model. Practical rules for the sensing parameter tuning are provided with reference to the considered mobility models. The analytical results are finally validated through simulations.

Cooperative spectrum sensing techniques are mainly based on two different decision approaches, according to the role of the decision maker: i) in the Combining Decision approach, the decision maker combines the sensing information collected from its cooperators, without participating in the sensing of the monitored band; ii) in the Sensing & Combining Decision approach, the decision maker combines both the sensing information of its cooperators and its own local sensing information. The choice of the decision approach deeply affects the performance of any cooperative spectrum sensing technique. However, the key issue of choosing the decision approach that guarantees the higher detection accuracy independently of the underlying cooperative sensing architecture is still an open problem. For this, in this paper, the criteria for an effective decision-approach selection are analytically derived with the object of maximizing the detection accuracy in presence of realistic channel propagation effects. Specifically, through a theoretical analysis, it is proven that the detection accuracy exhibits a threshold behavior as a function of the adopted decision approach. Closed-form expressions of such a threshold are analytically derived and practical insights for the decision approach choice are provided. Finally, the theoretical analysis is validated through simulations.

This paper develops a solution for the problem of uncorrelated user selection in mobile cognitive radio ad hoc networks, with the objective to increase the performance of cooperative spectrum sensing. For this, a fully distributed user selection algorithm is developed by adaptively selecting uncorrelated cognitive radio users, which is able to account for dynamic changes in the network topology and in the channel conditions. Since the proposed user selection is based on the evaluation of the correlation experienced by the cognitive radio users, it is mandatory to have a parameter able to measure the correlation among them. For this, a spatial correlation coefficient is proposed to express the correlation characteristics of mobile cognitive radio users in different environments. Performance evaluation is conducted through simulations, and the results reveal the benefits of adopting the proposed correlation-aware user selection for cooperative spectrum sensing.

In this paper, the effects of the primary-user (PU) mobility on spectrum sensing in Cognitive Radio (CR) networks are studied. To this aim, first, the spectrum sensing problem is reformulated to account for the PU mobility. Then, the effects of the PU mobility are studied with the objective to determine the parameters that affect the spectrum sensing functionality. For this, two performance metrics are analytically derived: i) the detection capability, which measures the PU mobility impact on the CR user detection probability; ii) the mobility-enabled sensing capacity, a new metric that measures the expected transmission capacity achievable by a CR user in the presence of PU mobility. The mathematical analysis is carried out in different scenarios, by using mobility and spectrum occupancy models. The results show that the detection capability is affected by five parameters: the PU protection range, the network region size, the PU mobility model, the CR spatial distribution, and the number of PUs that use the same spectrum band. Moreover, it is shown that the sensing capacity can significantly increase in the presence of PU mobility if the PU protection range is smaller than the network region size. The mathematical results are derived by considering the dynamic PU traffic, and validated through simulations.

Cooperative approaches have been proposed as an effective way to improve the spectrum sensing accuracy. Generally, cooperative spectrum sensing techniques require two successive stages: sensing and reporting. The reporting channels are usually assumed ideal. In this paper, we remove this assumption and we investigate the effects of reporting channels affected by temporal dispersion on cooperative spectrum sensing. To this aim, we propose two fusion schemes: a Widely Linear scheme and a Linear one. For both the schemes, closed-form expressions of the detection and the false alarm probabilities are derived. The performance are also evaluated numerically, and the results show that the Widely Linear detector outperforms the Linear one in operative conditions of practical interest. Moreover, for the sake of completeness, a theoretical comparison of the proposed detectors is carried out for reporting channels affected by multipath frequency non-selective fading. Surprisingly, the analysis proves that the two detectors perform exactly the same under this assumption. Therefore, there is not anymore advantage in using the Widely Linear scheme, which exhibits higher, although limited, computational complexity. The theoretical analysis is validated numerically.

The Spectrum Sensing is a fundamental functionality of the Cognitive Radio (CR) paradigm since a reliable detection of the presence of spectral holes is a mandatory requirement to avoid harmful interferences to licensed users. In this paper, we address this problem by proposing a widely linear (WL) cooperative strategy at a fusion center side where the CR user statistics have been received by means of multipath fading channels. The proposed strategy jointly elaborates the received signal and its conjugate version to take advantage by the information contained in the statistical pseudo-covariance function of the received signal. We design the WL strategy to maximize a modified deflection coefficient and we compare it with a strictly linear (SL) cooperative strategy. Results of numerical simulations show that the WL fusion-rule outperforms the SL one in operative conditions of practical interest.

In this paper we address the issue of the optimal candidate-set selection in the opportunistic routing paradigm. More specifically, although several algorithms for selecting the optimal candidate set have been proposed, to the best of our knowledge none of them has never considered the problem of selecting the optimal constrained candidate set, namely the optimal candidate set with a fixed maximum set size. In this paper we contribute to this problem by providing an analytical framework to model both the optimal constrained and unconstrained candidate-set selection. Moreover, we propose two algorithms for optimal candidate-set selection for distance vector routing, one for the constrained and one for the unconstrained case. Simulations based on experimental data validate our proposal.

In this letter, the constant-modulus (CM) cost function is analyzed under the general assumptions that improper modulation schemes of practical interest are employed and the baseband equivalent of the channel impulse response is complex-valued. This study allows one to determine a broad family of undesired minima of the CM cost function, which do not lead to perfect symbol recovery in the absence of noise. The results developed herein generalize and subsume as a particular case existing studies of the CM cost function, which exclusively consider real-valued binary modulations.