The rise of quantum computing poses a major threat to traditional ciphers, specifically making the Radio Access Network (RAN) vulnerable to future quantum-based attacks. To address this challenge, this paper proposes quantum-inspired RAN (Q-RAN), a next-generation framework designed to future-proof telecom networks against quantum threats. As a foundation, to evaluate, we integrate quantum network simulators with the Open-Source OpenAirInterface (OAI) stack to deploy a 5G standalone network capable of supporting quantum operations. We analyzed these, and the best fit is taken for quantum proofing. This paper considered four different quantum simulators — QuNetSim, SimQN, SeQuence, and NetSquid — for integrating with the 5G Open source stack. The framework generated by these simulators is called Quantum Gateways (namely Qtunnels) enables seamless message exchange between quantum and classical RAN components. This integrated architecture showcases how quantum simulators can be harmonized on existing 5G infrastructure, establishing a resilient and adaptable telco ecosystem catered to the quantum era or post-quantum era. In addition, this paper quantifies the Qtunnel impact — F1 Interface — between the Central Unit (CU) and Distribution Unit (DU) of RAN. The results show that the Post Quantum Cryptography (PQC)-enabled F1 interfaces provide a two-fold overhead delay when compared to the benchmark delay, however, the PQC-enabled RAN interfaces are resistant to quantum threats.

In today’s fast-evolving technological landscape, the Internet of Things (IoT) is fundamentally reshaping how systems connect, interact, and exchange data. As billions of devices become interconnected, the IoT brings both unprecedented opportunities and significant challenges across various domains. Emerging technologies, particularly quantum communication networks, offer transformative solutions by enabling ultra-secure data exchange within IoT infrastructures through advanced techniques such as Quantum Key Distribution (QKD). However, quantum link delay remains one of the key challenges that hinder the effective utilization of these networks. Traffic engineering is a robust method to address this challenge and optimize the performance of quantum networks. This technique involves assessing the current state of the network and making dynamic adjustments based on real-time conditions. Despite its proven benefits in classical systems, its role in quantum networks remains largely unexplored, with no comprehensive framework to date. As a result, in this paper, we propose a framework for quantum traffic engineering and discuss its core components—non-invasive measurements, quantum traffic matrices, data analysis, and performance control. Additionally, we integrate the Particle Swarm Optimization (PSO) algorithm into our framework to minimize the quantum link delay. Ultimately, this work establishes the foundation for researchers in quantum network traffic engineering and sets the stage for continuous, and dynamic monitoring of these networks.

In today’s fast-evolving technological landscape, the Internet of Things (IoT) is fundamentally reshaping how systems connect, interact, and exchange data. As billions of devices become interconnected, the Internet of Things brings unprecedented opportunities and significant challenges in various domains. Emerging technologies, particularly quantum communication networks, offer transformative solutions by enabling ultra-secure data exchange within IoT infrastructures through advanced techniques such as quantum key distribution. However, a significant obstacle to the efficient use of these networks is the lack of current status knowledge of network parameters, which is essential for continuous and dynamic management through quantum traffic engineering. In this paper, we propose the novel concept of quantum traffic matrices as a foundational framework to capture the dynamic operational state of quantum networks. We begin by distinguishing classical traffic matrices from their quantum counterparts. We then identify and present mathematical models for eleven key quantum network parameters that are essential to enable continuous and dynamic management of quantum networks. Our approach and results serve as crucial input for the development of quantum traffic engineering strategies, paving the way for intelligent control, optimization, and resilience enhancement of future quantum communication infrastructures.

The key features of 5G, particularly URLLC and mMTC, are designed to achieve low latency and high scalability. To support these requirements, a proposed approach for random access scenarios, known as the GF scheme, eliminates handshakes between the BS and mobile users to reduce latency and accommodate a large number of devices. However, this introduces a new challenge known as AUD, where users send messages indicating their activity status, requiring the BS to detect and decode them. Decoding these messages, however, demands high computational complexity, which increases exponentially with the number of users. Several algorithms, such as ZF and CCR, have been proposed to mitigate this complexity, but they suffer from suboptimal performance. On the other hand, the optimal solution, known as ML, performs well but suffers from high complexity. To address this, quantum algorithms, like Grover's algorithm, have been proposed due to their ability to reduce search complexity while also keep detecting active users performance better. However, Grover's algorithm requires adaptation in this context, as the optimal number of iterations depends on the number of solutions, which is always unknown in the AUD case. To address this, the BBHT and DHA algorithms have been proposed to minimize complexity when the solution is unknown, but both still exhibit relatively high computational demands. In this paper, we propose an Enhanced BBHT that aims to reduce this complexity while maintaining detection performance. Our findings demonstrate that the Enhanced BBHT reduces computational complexity while keeping the performance stable.

The security of the Internet of Things has emerged as a critical concern in the age of interconnectivity. Quantum computers pose a threat to the public key-based Rivest-Shamir Adleman methods currently utilized in encryption. Quantum keys, which can create a Quantum Key Distribution network based security protection system for the quantum Internet of Things, can theoretically provide unconditional security. Among these technologies, Continuous Variable Quantum Key Distribution is currently experiencing rapid and significant growth. This can be attributed to its capacity to support multiple channels and its ease of integration into current optical communication networks. However, the absence of an efficient key allocation system may waste the generation of quantum keys and decrease the overall quality of service. As a result, this paper proposes a Quantum Key Management scheme based on continuous variable Quantum source and application scenarios. The scheme allocates quantum keys from the quantum source. Quantitatively weights the security requirements of key requests in proportion to the quantum key. Our findings indicate that the system successfully manages the keys; however, excessive network traffic can overwhelm the system’s capabilities, leading to increased errors. This underscores the importance of optimizing traffic load to ensure reliable Continuous Variable Quantum Key Distribution

While routing methods in the literature often assume the use of quantum memory, this study proposes a routing algorithm designed for memoryless quantum networks. The algorithm leverages lexicographic optimization principles to hierarchically prioritize and optimize multiple objectives such as distance and capacity. This approach identifies the shortest paths between source-destination pairs within the decoherence time and selects a path that satisfies the minimum capacity require ments. To prevent entanglement fidelity from dropping below the desired threshold, purification is applied. Simulation results demonstrate the algorithm’s ability to manage latency while enhancing throughput effectively. The study comprehensively analyzes performance metrics under varying capacity values, request numbers, and threshold fidelity levels. Additionally, to the best of our knowledge, it is the first study to calculate latency, including queuing delay, in the context of quantum networks. Future research aims to explore optimal threshold fidelity values that balance throughput and latency performance.

With the increasing security demands of nextgeneration communication standards and the looming threat posed by quantum computers to traditional encryption methods, quantum key distribution (QKD) has emerged as a promising solution in domains such as military, government, and finance, with significant potential for further commercialization. Although QKD is theoretically unconditional secure, practical implementations often face vulnerabilities arising from imperfections in channels and devices, as well as inherent characteristics of QKD protocols. This paper investigates the probability of eavesdropping from the perspective of error rates using probabilistic analysis. Such an approach not only facilitates the detection of potential eavesdropping but also helps estimate the amount of leaked information, providing a basis for subsequent countermeasures like privacy amplification. Additionally, the probabilistic analysis sheds light on the robustness of communication channels with varying quality against eavesdropping attempts.

Evolution towards 6G communication networks aims to support burgeoning alternative technologies in order to overcome traditional classical trade-offs in various aspects of network performance, security, and latency. With this pursuit also striving to meet more nuanced aspects of purported trustwor-thiness standards, the soaring complexity of the next-generation networks is unsurprising; additional classical resources (third-party random number generators, pre-shared keys, etc.) are thus becoming increasingly relied upon for optimal network functioning. In this paper, we explore the potential of quantum technology and how it might be possible to utilize quantum phenomena like quantum entanglement to transfer decisional information in specific network contexts while also inherently providing destination anonymity without requiring additional classical resources.

Routing plays a pivotal role in quantum communication as it directly impacts the efficiency, reliability, and scalability of quantum networks. While several studies in the literature have explored routing algorithms leveraging quantum memories, current quantum memory technologies are unable to simultaneously achieve high fidelity, extended storage durations, wide bandwidths, multimode capacity, and high efficiency. To address this limitation, our study focuses on fidelity-guaranteed entanglement routing within a memoryless network architecture, employing both distributed and centralized routing approaches. Utilizing our proposed routing algorithm, MEFID, we achieved a throughput of 72 qubits per second under a fidelity threshold of 0.8 and within three iterative rounds. By integrating a purification process to ensure that the final fidelity consistently exceeds the specified threshold, our algorithm facilitates the development of robust and high-performance quantum networks.

The application of hybrid scheduling for both conventional data transmission and quantum key distribution (QKD) in next-generation hybrid 6G networks is examined in this research. The study simulates transmission over Multimode Fiber (MMF), where QKD keys and classical packets are sent in parallel without a scheduler, and over Single-Mode Fiber (SMF) utilizing time-based and event-based scheduling protocols. Bit Error Rate (BER) and Packet Error Rate (PER) comparisons between the two protocols show improvements in latency and resource allocation efficiency achieved by the SMF scheduler. Concurrent transmission of classical and quantum offers the possibility of boosting data throughput. The effect of cross-talk coefficient on the accuracy of transmitted data is also elaborated. These findings highlight the necessity for customized methods in hybrid quantum-classical networks by shedding light on the performance and adaptability of scheduling techniques on SMF and the advantages of space division multiplexing on MMF. For MMF specifically it showcases noise resistance quantum data transmission.

Routing is essential for quantum communication since it controls the effectiveness, dependability, and scalability of quantum networks. Although research on routing algorithms using quantum memories has been published in the literature, there aren't any quantum memories that can simultaneously achieve high fidelity, long storage duration, wide bandwidth, multimode capacity, and high efficiency. Therefore, in this study, we developed the fidelity-guaranteed MEDIRA routing algorithm, utilizing a distributed routing approach in a memoryless quantum network. As a result of the algorithm, we achieve a throughput of 17.2 qubits per second, for a demand fixed between 1 and 20. To the best of our knowledge, this is the first work that utilizes a queuing approach in a memoryless distributed routing algorithm with fidelity assurance.

In-Network Computing has brought computing and communication together at every communication node in the digital world, this work lays the foundations for doing the same in the quantum world, improving communication properties in the process - a combination of quantum computing and quantum communication. Full network softwarization, in-network intelligence, and massive connectivity will create an unprecedented demand for computing resources in the digital world. Accordingly, the scientific and industrial communities have begun to explore technologies such as quantum computing and have made significant efforts to demonstrate an algorithmic advantage for various problems. However, practical quantum computers are resource-inefficient and difficult to build. This article introduces a new communication paradigm leading to the concept of quantum in-network computing in the context of entanglement-assisted communication and computing for inherent distributed resilience and sensing. We review the fundamentals of digital hardware as characterized by Turing’s computability theory and demonstrate their relevance to mathematically rigorous characterizations of gate-based quantum computing. We then provide such a characterization using methods from effective analysis, leading to significant results that reveal the inherent theoretical limitations of universal gate-based quantum computers. These results support our assessment that gate-based quantum in-network computing is only possible through specialized, non-universal solutions that are seamlessly integrated with high-performance digital computing.

Network Modularization, i.e., the refactoring of the functionalities of 5G Network Functions (NFs), will be an important tool to meet future requirements in the 6G System (6GS). In particular, via network modularization, it is possible to streamline the NF compositions and the inter-Nfinteractions. However, to achieve the highest possible efficiency without loss on inter-operability, we need a clear understanding of the different Key Performance Indicators (KPIs) and modularization techniques which are required to achieve the necessary end-to-end performance. In this work, we investigate the KPIs, the modularization methods prioritized by the research community, and the industrial implications thereof. We also outline the or-chestration requirements for the successful integration of modules to 6GS and the one possible integration of quantum technology to solve the synchronization challenge.

Time synchronization is crucial in the architecture of modern communication networks, supporting numerous high-stakes applications like financial transactions, autonomous vehicle control, and data center operations. While traditional time synchronization protocols, specifically the Network Time Protocol (NTP) and Precision Time Protocol (PTP), are reliable for various applications, they fall short in scenarios requiring ultra-high precision and resilience. To address these limitations, this paper provides a comprehensive comparative analysis of two emerging quantum technologies, namely Time-Correlated Entangled Photons (TCEP) and Optical Lattice Clocks (OLC). Using Monte Carlo simulations, we examined the synchronization in terms of the accuracy of these technologies under various noise conditions, revealing that while TCEP works perfectly in low-noise environments, its efficacy diminishes significantly with increasing noise levels. On the contrary, OLCs demonstrate consistent performance across various noise levels, making them more versatile for diverse application scenarios. This study is foundational for integrating quantum technologies in time synchronization for communication networks and sheds light on their merits and challenges. Our findings open new avenues for research in scalability, environmental resilience, and the development of hybrid quantum-classical timekeeping systems. Integrating quantum-enhanced time synchronization into a communication network will be the key step for achieving full-fledged Quantum Internet and quantum-enhanced communication networks.

Microservice architecture is a service-oriented paradigm that enables the decomposition of cumbersome monolithic-based software systems. Using microservice design principles, it is possible to develop flexible, scalable, reusable, and loosely coupled software that could be containerized and deployed in a distributed edge/cloud environment. The flexible deployment of microservices in an edge environment increases system performance in terms due to dynamic service function placement and chaining possibly resulting in latency reduction, fault tolerance, scalability, efficient resource utilization, cost reduction, and energy consumption reduction. On the other hand, virtualization and containerization of microservices add processing and communication overheads. Therefore, to evaluate end-to-end microservices-based system performance, we need to have an end-to-end mathematical formulation of the overall microservice-based network system. Incorporating the virtualization overhead, here we provide end-to-end mathematical formulation considering system parameters: latency, throughput, computational resource usage, and energy consumption. We then evaluate the formulation in a testbed environment with the Microservice-based SDN (MSN) framework that decomposes the Software-defined Networking (SDN) controller in microservices with Docker Container. The final result validates the presented mathematical modeling of the system’s dynamic behavior which can be used to design a microservice-based system.

The generation of random numbers and the study of its properties have been an elusive field for a fair portion of the century. The application of random numbers is employed in many use cases such as cryptography, neural networks, numerical simulation, and gambling. The performance of each of these use cases is profoundly impacted by the employed random numbers; henceforth, the quality of randomness is of critical importance when it comes to their usage. A poorly generated random number can make a security system vulnerable, or any numerical or statistical evaluation misleading. Although various modes of classical random number generators exist and still function to provide strong cryptographic properties, emergence of quantum mechanical randomness has shed light on a novel path of generating certified randomness which supersedes the classical counterpart in terms of security. Harnessing quantum mechanical phenomena enables generation of true random numbers which can be certified and further implemented to elevate the net quality of the specific use cases. In this work, we generate and analyze random numbers from three different sources — 50: 50 beam splitter (BS), quantum key distribution (QKD) setup with classical post-processing scheme, and a commercially available quantum random number generator (QRNG) (ID Quantique (IDQ)). The quality of the generated random numbers from the various sources is checked in statistical tests and compared. Further on, we have developed a system which implements the QRNG-based random numbers to facilitate message authentication code (MAC) and one time password (OTP) protocols, demonstrating a communication network application. In this manner we discuss about a network which integrates quantum mechanics to the current classical networking approaches to enhance certain aspects of the networking protocol — in this case, the security.

This study focuses on the innovative field of quantum synchronization for satellite-based navigation systems including Global Navigation Satellite Systems (GNSSs) and the Non-Terrestrial Network (NTN) component of future 6G networks integrating both communication and navigation services. By combining a four-qubit system with the theoretical approach of the Lindblad master equation, we transcend the inherent limits of standard synchronization techniques. This achievement represents a quantum leap in satellite-based positioning, highlighting the scalability and cost-effectiveness of our technique for smaller satellites. The study demonstrates the possibility of reducing synchronization errors to less than one meter, significantly improving the reliability and precision of satellite-based navigation systems. The results of this study may contribute to the future development of both user-centric localization systems (typically GNSS systems) and network-centric localization systems (typically through the NTN component of 6G networks), leading to better positioning performance, more flexible multi-functional systems with the potential to limit both cost and size of satellites.

In a communication scenario with two transceivers (TRXs) and one relay, four time slots are required to communicate one packet in each direction if the relay uses a store-and-forward technique. With digital network coding (NC) three time slots are needed, and if analog netwok coding (ANC) is used, only two time slots are necessary. Communication systems with a low transmission rate such as molecular communication (MC) systems can especially benefit from the traffic reduction of ANC. The available literature only considers theoretical studies on the application of NC in MC nanonetworks. In this paper, we present for the first time a macroscale MC testbed for ANC to fill the gap between theory and practice. By using our testbed, we demonstrate the influence of time synchronization on the bit error ratio (BER) performance of the network coded MC system. We also study the influence of the bit sequence length on the error ratio of the system. Furthermore, we implemented duplex NC and demonstrated that the error ratios of half duplex and full duplex NC are close, but full duplex NC results in a time gain of up to$(n-1)$time slots for a bit sequence length n.

Applying renewable energy in a smart micro grid (MG) is increasingly receiving attention to reduce greenhouse gas emissions. However, the mismatch between supply and demand hinders the realization of this process. With the widespread use of plug-in electric vehicles (EVs) and the development of emerging mobile edge cloud (MEC), intelligent energy optimization becomes a way to address the challenge. Therefore, in this paper, we propose a novel two-stage approach based on deep learning (DL) to reduce overall energy cost for sharing EVs integrated MG by forecasting its state and optimizing EVs scheduling. Our simulation results show that the joint design of forecasting and optimization reduces the overall energy consumption and the payment to the external grid.

Data privacy concerns are increasing significantly in the context of the Internet of Things, cloud services, edge computing, artificial intelligence applications, and other applications enabled by next-generation networks. Homomorphic encryption addresses privacy challenges by enabling multiple operations to be performed on encrypted messages without decryption. This article comprehensively addresses homomorphic encryption from both theoretical and practical perspectives. This article delves into the mathematical foundations required to understand fully homomorphic encryption ($\textsf {FHE}$). It consequently covers design fundamentals and security properties of$\textsf {FHE}$and describes the main$\textsf {FHE}$schemes based on various mathematical problems. On a more practical level, this article presents a view on privacy-preserving machine learning using homomorphic encryption and then surveys$\textsf {FHE}$at length from an engineering angle, covering the potential application of$\textsf {FHE}$in fog computing and cloud computing services. It also provides a comprehensive analysis of existing state-of-the-art$\textsf {FHE}$libraries and tools, implemented in software and hardware, and the performance thereof.

An autonomic network management system (ANMS) is expected to play a significant role in fifth and sixth-generation (5G and 6G) networks. It enables the network to manage itself with minimum or no human intervention. Recently, an ANMS architecture called multi-agent-based network automation of the network management system (MANA-NMS) architecture was presented. The article discussed a multi-agent service decomposition architecture, defining atomic network-functions (ANFs). These ANFs are proposed to be intelligent and autonomous agents. The agents are designed as independent atomic decision elements incorporating machine learning (ML) as an internal cognitive component. The atomic units are used as a building block for an ANMS. In line with this approach, this article proposes a network traffic classifier agent (NTCA) as a part of the network traffic management system. We first design and implement a NTCA using an ML algorithm as a cognitive component of the agent. To compare, we used K-Nearest Neighbors (K-NN), Decision Tree, Support Vector Machine (SVM), and Naive Bayes in the agent design. We perform an evaluation using classification accuracy, training latency, and classification latency. Finally, we tested the performance of the NTCA by implementing it in the MANA-NMS conceptual framework. The results show that the Decision Tree NTCA has the highest mean classification accuracy, the least mean training latency, and the lowest mean classification latency.

Internet of Things (IoT) network is dominating both the research and industry. There are numerous emerging IoT connectivity Technologies such as Sigfox, LoRa, NB-IoT, LTEM. However, these IoT connectivity technologies have different protocols and packet/message formatting. Thus, IoT devices are usually not able to interact with one another, causing interoper-ability challenges. This is creating the so-called network island or silos. Interoperability between different IoT networks needs to be achieved to fully exploit IoT potential. This is required at each level of the network. Different solutions have been proposed to tackle the interoperability problem at different levels reducing the difficulty in defining a solution breaching the vertical silos barrier. In this article, we focus on addressing network-level interoperability. We provide a network format translator in a virtualized environment as a flexible and lightweight deployment. As a proof of concept, a testbed is developed implementing the proposed translator using NS3. Using the testbed, we can communicate with different IoT technologies sending packets between each device in each type of IoT network. For example, sending a LoRaWAN packet to Wi-Fi and 6LoWPAN and visa-versa. Finally, we have measured the latency introduced by the translator.

The introduction of the Internet of Things (IoT) and massive machine-type communications has implied an increase in network size and complexity. In particular, there is already a huge number of IoT devices in the market in various sectors, such as smart agriculture, smart city, smart home, smart transportation, etc. The IoT interconnectivity technologies are also increasing. Therefore, these are increasingly overwhelming the efforts of network administrators as they try to design, reconfigure and manage such networks. Relying on humans to manage such complex and dynamic networks is becoming unsustainable. Network automation promises to reduce the cost of administration and maintenance of network infrastructure, by offering networks the capability to manage themselves. Network automation is the ability of the network to manage itself. Various standardization organizations are taking the initiative in introducing network automation, such as European Telecommunication Standardization Institute (ETSI). ETSI is leading the standardization activities for network automation. It has provided different versions of reference architecture called generic autonomic network architecture (GANA), which describes a four-level abstraction for network-management decision elements (DEs), protocol level, function level, node level, and network level. In this article, we review and survey the existing works before and after the introduction of software-defined networking (SDN) and network-function-virtualization (NFV). We relate the main trending paradigms being followed, such as SDN, NFV, machine learning (ML), microservices, multiagent system (MAS), containerization, and cloudification, as a pivotal enabler of full network automation. We also discuss the autonomic architectures proposed in the literature. Finally, we presented possible future research directions and challenges that need to be tackled to progress in achieving full network automation.

The advent of network softwarization is enabling multiple innovative solutions through software-defined networking (SDN) and network function virtualization (NFV). Specifically, network softwarization paves the way for autonomic and intelligent networking, which has gained popularity in the research community. Along with the arrival of 5G and beyond, which interconnects billions of devices, the complexity of network management is significantly increasing both investments and operational costs. Autonomic networking is the creation of self-organizing, self-managing, and self-protecting networks, to afford the network management complexes and heterogeneous networks. To achieve full network automation, various aspects of networking need to be addressed. So, this article proposes a novel architecture for the multi-agent-based network automation of the network management system (MANA-NMS). The architecture rely on network function atomization, which defines atomic decision-making units. Such units could represent virtual network functions. These atomic units are autonomous and adaptive. First, the article presents a theoretical discussion of the challenges arisen by automating the decision-making process. Next, the proposed multi-agent system is presented along with its mathematical modeling. Finally, MANA-NMS architecture is mathematically evaluated from functionality, reliability, latency, and resource consumption performance perspectives.

5G and beyond need to meet stringent requirements of latency, reliability, and support for heterogeneous devices. However, the existing wireless network architecture is limited to fulfill these constraints. Cloud radio access network, along with network function virtualization, is suggested to provide flexibility and network agility. It decouples network functions, such as firewall and packet gateway, from hardware to software deployed in the cloud. Thus comprehensive end-to-end formulation of this architecture is required for virtual network function placement. Most of existing works focus on virtual functions placement with different objectives, addressing different service requirements separately. In this article, six 5G constraints are considered simultaneously to find optimal virtual network function placement with service differentiation. The selected six parameters reflect services' requirements, network constraints and computing constraints. We first model the overall cloud radio access network as a multi-layer loopless-random hypergraph and we provide the overall formulation of the system. Then, we reformulate such model considering backup virtual functions and CPU over-provisioning techniques to improve both virtual function's reliability and processing latency. Finally, we propose service differentiation to reduce CPU utilization and energy consumption, while using the above techniques. The results suggest that the application of service differentiation can significantly improve assignment of computing resources and energy efficiency.

Achieving the low‐latency constraints of public safety applications during disaster could be life‐saving. In the context of public safety scenarios, in this paper, we propose an efficient radio resource slicing algorithm that enables first responders to deliver their life‐saving activities effectively. We used the tool of stochastic geometry to model the base station distribution before and after a disaster. In addition, under this umbrella, we also proposed an example of public safety scenario, ultrareliable low‐latency file sharing, via in‐band device‐to‐device (D2D) communication. The example scenario is implemented in NS‐3. The simulation results show that radio resource slicing and prioritization of first responders resources can ensure ultrareliable low‐latency communication (URLLC) in emergency scenarios.

5G wireless communication envisions unprecedented changes in current mobile networks in order to guarantee significant higher performance mainly in terms of data rates, latencies and efficiency. This paper provides an analytical model based on stochastic geometry, in order to address the planning and the dimensioning of 5G Cloud RAN. The results shows the requirements in terms of number of virtual base-band units, and the energy gain achieved by virtualisation both in micro-cell and pico-cell scenarios. Thus, the proposed methodology represents a step forward to analyse and compare traditional RAN design with the emerging Cloud RAN paradigm.

Information paths in current communication networks can often be modelled by set of serial links interconnected by intermediate nodes. These kind of scenarios are called line networks. If the links between nodes experience connection problems, burst erasures of information can happen. In this article, hybrid serial concatenated network codes are proposed, which consist in the serial concatenation of a 'classical' coding scheme and a network code. A novel way to decrease complexity of this approach is that the 'classical' coding scheme is not performed on a link level. The new coding schemes improve performance of the communications in line networks in terms of error- correcting capability. The evaluations involve MATLAB simulations and analytical analysis.

The diffusion of mobile devices, that are capable to play videos, opened new challenges for video streaming applications. Since wireless communications are prone to erasures, an important goal is to research possible ways to reliably provide video content. Fountain codes are an efficient way to protect video streaming against erasures: in particular, burst erasures are the ones that can significantly reduce the quality of the transmitted video. In this work, Luby codes for burst erasure channels are investigated. Our main focus is on the design of Luby codes to make the receiver able to recover all the lost information without any retransmission. Furthermore, we analytically demonstrate that lower energy consumption is achievable by using LT codes instead of a general retransmission scheme.

This paper studies the performance of network coding (NC) based system, especially looking at the implications in surveillance applications. We argue that NC can provide advantages from a data throughput perspective; however, an analysis of NC mechanism, especially when there are erroneous channels in the network, is required. We study the performance of the NC mechanism based on several parameters for different scenarios categorized by the error-free and erroneous communication channels that introduce random errors either at packet or at symbol level.