The growing complexity of cloud-native, edge, and IoT infrastructures has made manual configuration, fault remediation, and lifecycle management increasingly unsustainable. Traditional automation techniques—such as rule-based logic or bespoke machine learning pipelines—struggle with adaptability and explainability in dynamic environments. Recent advances in Large Language Models (LLMs), however, have introduced new opportunities for autonomous, intent-driven infrastructure control. In this work, we present a closed-loop framework that integrates LLM agents for automated Root Cause Analysis (RCA) and mitigation of faults within cloud-edge and IoT systems. When SLA violations are detected, the agent identifies likely root causes and selects corrective actions—such as pod rescheduling, scaling, or configuration updates—executed via a Model Context Protocol (MCP) server exposing management tool functionalities through an API. This RCA-plus-mitigation loop enables fault handling that is both explainable and adaptive. We evaluate our system on a cluster running synthetic IoT workloads under emulated stressors using a reproducible benchmarking setup. Results show that the agent identifies SLA violations with 52.9% accuracy and mitigates 70.7% of them successfully. Notably, the agent incorporates validation steps to ensure system stability after interventions. These findings highlight the feasibility of LLMs for real-time infrastructure healing and their potential role in future AIOps workflows.

In the realm of modern telecommunication ecosystems, resource-aware management is critical in ensuring quality of service (QoS) while enabling proactive, zero-touch operations. Furthermore, recent advances in software defined networking (SDN) have significantly contributed to beyond 5G (B5G) network optimization, offering innovative solutions to tackle their growing complexity. Moreover, the inherently non-convex nature of service provisioning challenges presents critical obstacles to delivering a seamless user experience. This paper introduces a novel framework that integrates Dueling Double Deep Q-Networks (Dueling DDQN) within a cloud-native edge infrastructure, enabling zero-touch service scaling. By harnessing the advanced capabilities of deep reinforcement learning (DRL), the proposed method autonomously identifies and addresses scaling demands, thereby improving overall network capabilities. The effectiveness of our approach is validated through experiments conducted on a multi-node Kubernetes testbed, demonstrating its ability to alleviate performance bottlenecks in distributed environments.

Advancement of edge and far-edge computing, driven by the increasing demand for real-time, data-intensive applications, has heightened the need for reliable and efficient resource management in volatile environments. This paper introduces GTMixer, a deep learning architecture tailored for predicting resource usage in volatile edge computing scenarios. GTMixer utilizes a Dynamic Temporal Graph (DTG) to capture the evolving interdependencies in workload exchanges across edge and far-edge nodes. By processing snapshots of this graph, GTMixer identifies patterns in resource utilization, even in the absence of historical CPU data. Our contributions include: (1) the creation of a DTG that reflects migration patterns and resource utilization among nodes; (2) the development of the GTMixer model, which integrates feature mixing with graph neural networks for improved predictive accuracy; and (3) empirically evaluating GTMixer against state-of-the-art models using a modified version of the Alibaba 2021 traces dataset that accounts for volatility. Our results demonstrate that GTMixer not only effectively anticipates resource requirements in unpredictable Multi-access Edge Computing (MEC) scenarios but also significantly outperforms current state-of-the-art models in terms of efficiency, showcasing its potential to enhance the reliability and performance of edge computing systems crucial for nextgeneration network technologies and applications.

As the demand for Network Function Virtualization accelerates, service providers are expected to advance the way they manage and orchestrate their network services to offer lower latency services to their future users. Modern services require complex data flows between Virtual Network Functions, placed in separate network domains, risking an increase in latency that compromises the offered latency constraints. This shift requires high levels of automation to deal with the scale and load of future networks. In this paper, we formulate the Service Function Chaining (SFC) placement problem and then we tackle it by introducing SCHEMA, a Distributed Reinforcement Learning (RL) algorithm that performs complex SFC orchestration for low latency services. We combine multiple RL agents with a Bidding Mechanism to enable scalability on multi-domain networks. Finally, we use a simulation model to evaluate SCHEMA, and we demonstrate its ability to obtain a 60.54% reduction of average service latency when compared to a centralised RL solution.

Artificial intelligence (AI)-driven zero-touch massive network slicing is envisioned to be a disruptive technology in beyond 5G (B5G)/6G, where tenancy would be extended to the final consumer in the form of advanced digital use-cases. In this paper, we propose a novel model-free deep reinforcement learning (DRL) framework, called collaborative statistical Actor-Critic (CS-AC) that enables a scalable and farsighted slice performance management in a 6G-like RAN scenario that is built upon mobile edge computing (MEC) and massive multiple-input multiple-output (mMIMO). In this intent, the proposed CS-AC targets the optimization of the latency cost under a long-term statistical service-level agreement (SLA). In particular, we consider the Q-th delay percentile SLA metric and enforce some slice-specific preset constraints on it. Moreover, to implement distributed learners, we propose a developed variant of soft Actor-Critic (SAC) with less hyperparameter sensitivity. Finally, we present numerical results to showcase the gain of the adopted approach on our built OpenAI-based network slicing environment and verify the performance in terms of latency, SLA Q-th percentile, and time efficiency. To the best of our knowledge, this is the first work that studies the feasibility of an AI-driven approach for massive network slicing under statistical SLA.

Artificial intelligence (AI)-driven zero-touch network slicing (NS) is a new paradigm enabling the automation of resource management and orchestration (MANO) in multi-tenant beyond 5G (B5G) networks. In this paper, we tackle the problem of cloud-RAN (C-RAN) joint slice admission control and resource allocation by first formulating it as a Markov decision process (MDP). We then invoke an advanced continuous deep reinforcement learning (DRL) method called twin delayed deep deterministic policy gradient (TD3) to solve it. In this intent, we introduce a multi-objective approach to make the central unit (CU) learn how to re-conFigure computing resources autonomously while minimizing latency, energy consumption and virtual network function (VNF) instantiation cost for each slice. Moreover, we build a complete 5G C-RAN network slicing environment using OpenAI Gym toolkit where, thanks to its standardized interface, it can be easily tested with different DRL schemes. Finally, we present extensive experimental results to showcase the gain of TD3 as well as the adopted multi-objective strategy in terms of achieved slice admission success rate, latency, energy saving and CPU utilization.

Emerging 5G communication paradigms, such as machine-type communication, have triggered an explosion in ad-hoc applications that require connectivity among the nodes of wireless networks. Ensuring a reliable network operation under fading conditions is not straightforward, as the transmission schemes and the network topology, i.e., uniform or clustered deployments, affect the performance and should be taken into account. Moreover, as the number of nodes increases, exploiting natural energy sources and wireless energy harvesting (WEH) could be the key to the elimination of maintenance costs while also boosting immensely the network lifetime. In this way, zero-energy wireless-powered sensor networks (WPSNs) could be achieved, if all components are powered by green sources. Hence, designing accurate mathematical models that capture the network behavior under these circumstances is necessary to provide a deeper comprehension of such networks. In this paper, we provide an analytical model for the connectivity in a large-scale zero-energy clustered WPSN under two common transmission schemes, namely, unicast and broadcast. The sensors are WEH-enabled, while the network components are solar-powered and employ a novel energy allocation algorithm. In our results, we evaluate the tradeoffs among the various scenarios via extensive simulations and identify the conditions that yield a fully connected zero-energy WPSN.

As wearables provide new health-related functionalities, they can be employed in hospitals to monitor patients and notify the medical personnel regarding their status. However, in order to be approved by the medical community, wearables need to have reliable communication and high lifetime. In such scenarios, it is important to know the probability of correct notification which is affected mainly by the deployment of the wireless wearables and their energy supply. Typically, rooms in hospitals host multiple people and, thus, a clustered communication model should be adopted for more trustworthy results. Moreover, by employing wireless charging, it is possible to provide an uninterrupted operation with high reliability. Therefore, in this paper, we study the aforementioned probability in a clustered network while the wearable devices are wirelessly charged. We provide an analytical model for the wearables' ability to inform quickly the medical personnel and discuss different trade-offs via extensive simulations.

The present paper studies fair sharing possibilities of stored renewable energy (RE) in densely populated areas among multiple mobile network operators (MNOs). The main objective is to enable MNOs, who already share their infrastructure in terms of a green network operation, to further reduce their power consumption by fairly sharing (i) the solar power harvested during daylight and (ii) the harvested energy that is stored in storage devices, e.g. batteries, during night hours. To this end, a bankruptcy game is designed so as to capture the energy sharing interactions among MNOs. Taking into consideration the energy deficits of each MNO for a studied period of time, Shapley Value (SV) is employed to fairly determine the amounts of energy to be allocated to each MNO. Focusing on night hours, it is shown that the proposed scheme provides all cooperative MNOs with long store-energy-based network operation during night in comparison to baseline schemes. Moreover, we display that the proposed scheme outperforms its counterparts in terms of needed grid support and allocation fairness among the cooperative MNOs for different MNO traffic patterns and volumes.

Facing the increasing energy demands associated with the perspective of fifth generation (5G) wireless networks, the Mobile Network Operators (MNOs) are motivated to gradually convert their traditional Radio Access Network (RAN) infrastructure to more flexible and power efficient centralized architectures, i.e., Cloud-RAN (C-RAN). Apart from their promising benefits in terms of management and network optimization, these new architectures further enable the sharing of spectrum and network elements, such as the Remote Radio Heads (RRHs) and the Baseband Units (BBUs), among multiple operators. In this paper, we introduce a novel scheme based on coalitional game theory to identify the potential room for cooperation among different MNOs that provide service to the same area. The proposed scheme sets the rules for profitable collaboration and identifies the core formation conditions (i.e., pricing) for various scenarios with different market and spectrum shares among three operators. Our results show that i) cooperation among subcoalitions of MNOs is always beneficial, yielding both higher revenues and enhanced Quality of Service (QoS) for the end users, and ii) the cooperation of all operators (grand coalition) is profitable for given user pricing in different scenarios.

The Energy Harvesting-aware Distributed Queuing access protocol (EH-DQ) is presented in this paper as a novel Medium Access Control protocol for wireless Machineto-Machine networks with energy harvesting capabilities. EHDQ is theoretically modeled to analyze its performance. A performance comparison with a Time Division Multiple Access (TDMA) and an EH-aware Reservation Dynamic Frame SlottedALOHA (EH-RDFSA) shows its superior performance. While TDMA requires updated network information to maintain a collision-free schedule and EH-RDFSA requires to estimate the number of contenders per frame to dynamically adjust the frame length, EH-DQ uses short and fixed frame lengths and does not require knowledge of the network topology or the number of end-devices in advance.

We demonstrate for the first time an analytical model for computing the end to end packet delay of an Optical/Wireless 60GHz Radio-over-Fiber (RoF) network operating under the Medium-Transparent MAC (MT-MAC) protocol. The model takes into account contention both at the optical and the wireless layer, effectively incorporating the MT-MAC mechanism for seamless and dynamic capacity allocation over both optical and wireless transmission media. Based on this model, we provide an extensive delay performance analysis of the Medium Transparent MAC protocol for various optical capacity availability scenarios, varying load conditions and optical network fiber lengths. The theoretical results are found to be in good agreement with respective simulation-based findings, confirming that the employment of Medium Transparent MAC protocols can allow for efficient incorporation of the MT-MAC scheme into the upcoming era of 5G mm-wave small-cell networks.

The emerging Internet of Things paradigm has triggered an explosion in ad-hoc applications that require connectivity among the nodes of wireless networks. However, the channel randomness and the random deployment of such networks could cause missed detections by isolated (i.e., unable to disseminate their messages) or inactive (i.e., without enough energy to transmit) nodes. Moreover, as the number of nodes increases, the use of “green” solutions such as wireless energy harvesting for powering battery-less devices could eliminate the maintenance costs and boost immensely the network lifetime. In this paper, we study the connectivity in a wireless-powered sensor network (WPSN) with battery-less devices under two common routing schemes, namely unicast and broadcast. We provide an analytical model for the ability of a WPSN to be reliable and evaluate the trade-offs among the different scenarios via simulation.

The Energy Harvesting-aware Contention Treebased Access (EH-CTA) protocol is presented in this paper as a novel Medium Access Control (MAC) protocol for wireless Machine-to-Machine (M2M) networks where end-devices are equipped with energy harvesters. The protocol is theoretically modeled to analyze its performance. A performance comparison with an EH-aware Dynamic Frame Slotted-ALOHA (EH-DFSA) shows its superior performance. While EH-DFSA requires an estimation of the number of contenders per frame in order to dynamically adjust the frame length, EH-CTA uses short and fixed frame lengths. This ensures scalability and facilitates synchronization in highly dense M2M networks.

Contemporary technologies as implemented in the field of healthcare have provided the everyday clinical practice with a plethora of tools to be used in various settings. In this field, distributed and networked embedded systems, such as Wireless Sensor Networks (WSNs), are the most promising technology to achieve continuous monitoring of aged people for their own safety, without affecting their daily activities. WSN4QoL is a Marie Curie project involving academic and industrial partners from three EU countries, which aims to show how new WSNs-based technologies suit the specific requirements of pervasive healthcare applications. In particular, in this paper, the WSN4QoL's system architecture is presented as designed to exploit the Network Coding (NC) mechanisms to achieve energy efficiency in the wireless communications and distributed positioning solutions to locate patients in indoor home environments. The system has been validated through experimental activities using commercial off the shelf (COTS) WSN testbeds and medical devices prototypes offered by a commercial partner. Results demonstrate that NC helps in achieving substantial gains in terms of energy efficiency as compared to traditional relay mechanisms, while the proposed positioning solution is able to locate people in indoor environments at a sub-room accuracy level, without requiring any extra dedicated hardware.

Due to the dense small cell deployment to cope with the increased data traffic of fifth generation (5G) networks, the direct backhaul (BH) connection of all small cells to the core network becomes challenging. To that end, millimeter wave (mmWave) is a promising solution for cost-efficient high capacity small cell BH links. However, due to the severe signal attenuation at high frequencies, mmWave can provide good coverage only for short distances, thus favoring a multi-hop 5G BH architecture. In this context, user association that impacts both the network and user performance calls for BH-aware strategies. Hence, in this paper, we study the user association problem aiming at the joint energy and spectrum efficiency maximization of the network, without compromising the user quality of service. The problem is formulated as a generalized assignment problem, which considers the capacity and energy consumption both in the access network and BH links. Provided that the considered problem is shown to be NP-hard, we employ optimization techniques to obtain an upper bound on system performance. We also propose a low complexity algorithm, which is shown to outperform the state-of-the-art while achieving near-optimal performance.

Mobile data offloading has been proposed as a solution for the network congestion problem that is continuously aggravating due to the increase in mobile data demand. However, the majority of the state-of-the-art is focused on the downlink offloading, while the change of mobile user habits, like mobile content creation and uploading, makes uplink offloading a rising issue. In this work we focus on the uplink offloading using IP Flow Mobility (IFOM). IFOM allows a LTE mobile User Equipment (UE) to maintain two concurrent data streams, one through LTE and the other through WiFi access technology, that presents uplink limitations due to the inherent fairness design of IEEE 802.11 DCF by employing the CSMA/CA scheme with a binary exponential backoff algorithm. In this paper, we propose a weighted proportionally fair bandwidth allocation algorithm for the data volume that is being offloaded through WiFi, in conjunction with a pricing-based rate allocation for the rest of the data volume needs of the UEs that are transmitted through the LTE uplink. We aim to improve the energy efficiency of the UEs and to increase the offloaded data volume under the concurrent use of access technologies that IFOM allows. In the weighted proportionally fair WiFi bandwidth allocation, we consider both the different upload data needs of the UEs, along with their LTE spectrum efficiency and propose an access mechanism that improves the use of WiFi access in uplink offloading. In the LTE part, we propose a two-stage pricing-based rate allocation under both linear and exponential pricing approaches, aiming to satisfy all offloading UEs regarding their LTE uplink access. We theoretically analyse the proposed algorithms and evaluate their performance through simulations. We compare their performance with the 802.11 DCF access scheme and with a state-of-the-art access algorithm under different number of offloading UEs and for both linear and exponential pricing-based rate allocation for the LTE uplink. Through the evaluation of energy efficiency, offloading capabilities and throughput performance, we provide an improved uplink access scheme for UEs that operate with IFOM for uplink offloading.

As large-scale dense and often randomly deployed wireless sensor networks (WSNs) become widespread, local information exchange between colocated sets of nodes may play a significant role in handling the excessive traffic volume. Moreover, to account for the limited life-span of the wireless devices, harvesting the energy of the network transmissions provides significant benefits to the lifetime of such networks. In this paper, we study the performance of communication in dense networks with wireless energy harvesting (WEH)-enabled sensor nodes. In particular, we examine two different communication scenarios (direct and cooperative) for data exchange and we provide theoretical expressions for the probability of successful communication. Then, considering the importance of lifetime in WSNs, we employ state-of-the-art WEH techniques and realistic energy converters, quantifying the potential energy gains that can be achieved in the network. Our analytical derivations, which are validated by extensive Monte-Carlo simulations, highlight the importance of WEH in dense networks and identify the tradeoffs between the direct and cooperative communication scenarios.

Machine-to-Machine (M2M) networks allow enddevices to communicate without human intervention. Due to the high density of M2M networks, efficient Medium Access Control (MAC) protocols are required to manage the access to the channel. In this paper, we consider an M2M area network composed of hundreds of end-devices that periodically transmit data to a gateway. We evaluate the performance of two Medium Access Control (MAC) protocols based on Frame Slotted-ALOHA (FSA) with Successive Interference Cancellation(SIC): Intra-frame SIC-FSA and Inter-frame SIC-FSA. By means of computer-based simulations, we have compared the delay and energy performance with respect to conventional FSA. Results show that the average delay can be reduced in a 78% and 94% by using Intra-frame SIC-FSA and Inter-frame SIC-FSA, respectively, and the average energy consumed per end-device is reduced in 18% by using Intra-frame SIC-FSA, while Interframe SIC-FSA decreases the energy consumed per end-device in a 22%.

In this paper, we propose a solution to efficiently handle the initial access contention for highly dense LTE networks, which still represents a challenge in terms of the high number of devices associated to Machine Type Communications. The analysis is based on the fact that, as the radius of a LTE cell is larger, the number of available preambles generated from a single root sequence is reduced. The current access mechanism, based on frame-slotted ALOHA, does not operate efficiently under these conditions, negatively affecting the access delay and collision probability. We show how the access procedure can be improved by implementing tree-splitting algorithms in order to cope with high number of simultaneous arrivals in large cells, above 5 km in radius. The implementation achieves as much as 85% reduction on the access delay and 54% reduction on energy consumption for cells with radius larger than 39 km.

The dense deployment of high and low power nodes, i.e., eNodeBs (eNBs) and small cells (SCs), respectively, is expected to be the core element of fifth generation (5G) networks. Given the massive SC deployment, the aggregate power consumption attributed to SCs in the coverage area of a macrocell becomes considerable, thus raising issues for the network energy efficiency. However, the coexistence of multiple mobile network operators (MNOs) in the same geographic area fosters cooperation agreements that suggest further energy and cost saving. In this paper, with a view to address the aforementioned issues, we attempt to study the energy efficiency aspects in the case of next generation outdoor Long Term Evolution (LTE) heterogeneous networks (HetNets) owned by rival MNOs. More specifically, we propose a cooperative switching off scheme for low-traffic hours that applies to both eNBs and SCs and exploits roaming-based infrastructure sharing to guarantee the provided quality of service (QoS). To gain insights, we study the energy consumption impact compared to existing switching off schemes. It is shown that the proposed scheme achieves notable energy saving, without compromising the QoS to the network users.

As the number of nodes in wireless sensor networks (WSNs) increases, new challenges have to be faced in order to maintain their performance. A fundamental requirement of several applications is the correct transmission of the measurements to their final destinations. Thus, it is crucial to guarantee a high probability of connectivity, which characterizes the ability of every node to report to the fusion center. This network metric is strongly affected by both the fading characteristics and the different routing protocols that are used for the dissemination of data. In this paper, we study the probability of a network to be fully connected for two widely employed routing mechanisms, namely unicast and K-anycast. The analytical derivations and the simulations evaluate the trade-offs among the different routing mechanisms and provide useful guidelines on the design of WSNs.

In this paper we focus on the uplink offloading based on IP Flow Mobility (IFOM). With IFOM a User Equipment (UE) is able to maintain concurrently two data streams, one through LTE and the other through WiFi. We propose a weighted proportionally fair algorithm for the WiFi access and a linear pricing based algorithm for the LTE access. The existence of a malicious UE is considered that aims to exploit the WiFi bandwidth against its peers in order to upload less data through the energy demanding LTE uplink and a reputation based method is proposed to combat its selfish operation. We theoretically analyse our approach and evaluate the performance of the malicious and the truthful UEs in terms of energy efficiency through simulations. We show that while the malicious UE presents better energy efficiency before being detected, its performance is significantly degraded with the proposed reaction method.

We consider a wireless Machine-to-Machine (M2M) area network where a gateway periodically collects data from a group of end-devices equipped with energy harvesters. While the use of energy harvesters ideally provides infinite lifetime, the unpredictable amount of harvested energy may not guarantee that all data transmissions can be done in due time because of temporary energy shortages. We propose in this paper the Energy Harvesting-aware Reservation Dynamic Frame Slotted-ALOHA (EH-RDFSA) protocol as a solution suitable for managing the access of end-devices that transmit bursts of data packets while taking into account the energy availability. We derive a model based on a discrete-time Markov chain to analyze the evolution of the energy available in an end-device and to evaluate the performance of the network. In particular, we compute the data delivery ratio, which measures the ability of the protocol to successfully transmit data to the gateway without depleting the energy reserves of the end-devices, and the time efficiency, which measures the amount of data that can be transmitted in a given period of time. We have validated the accuracy of the analysis by means of computer-based simulations. Results show that the overall performance is influenced by the energy harvesting rate and the amount of data to transmit from each end-device. Finally, we have compared the performance of EH-RDFSA with that of DFSA and Time Division Multiple Access (TDMA) protocols.

In this paper, we address the challenge of high device density performing simultaneous transmissions by proposing and evaluating a solution to efficiently handle the initial access contention for highly dense LTE networks. We present the implementation of a tree-splitting algorithm in the access procedure of LTE, which is capable to cope with high number of simultaneous arrivals. Based on simulations we show a feasible implementation capable to achieve, under certain network configuration conditions, up to 85% average access delay reduction and 40% reduction on the average energy consumption, while maintaining a consistently low blocking probability, regardless of the number of initial simultaneous access attempts.

Wireless body area networks (WBANs) are composed of sensors that either monitor and transmit vital signals or act as relays that forward the received data to a body node coordinator (BNC). In this paper, we introduce an energy efficient vital signal telemonitoring scheme, which exploits compressed sensing (CS) for low-complexity signal compression/reconstruction and distributed cooperation for reliable data transmission to the BNC. More specifically, we introduce a cooperative compressed sensing (CCS) approach, which increases the energy efficiency of WBANs by exploiting the benefits of random linear network coding (RLNC). We study the energy efficiency of RLNC and compare it with the store-and-forward (FW) protocol. Our mathematical analysis shows that the gain introduced by RLNC increases as the link failure rate increases, especially in practical scenarios with a limited number of relays. Furthermore, we propose a reconstruction algorithm that further enhances the benefits of RLNC by exploiting key characteristics of vital signals. With the aid of electrocardiographic (ECG) and electroencephalographic (EEG) data available in medical databases, extensive simulation results are illustrated, which validate our theoretical findings and show that the proposed recovery algorithm increases the energy efficiency of the body sensor nodes by 40% compared to conventional CS-based reconstruction methods.

The explosive data traffic demands stress the need for additional capacity in cellular systems, which can be achieved through the exploitation of Small Cells (SCs). However, the deployment of SCs implies higher energy consumption in the network, something that translates into higher financial cost for the operators. To that end, the existence of a third party that provides a common SC infrastructure for the operators has been introduced as an appealing "green" solution, raising though important issues with regard to the cost sharing for the operators. In this paper, we effectively address this issue by proposing an accurate cost model for the SCs and employing different state-of-the-art techniques to share this cost. In addition, taking into account the impact of the traffic pattern on this cost, we propose a novel hybrid cost sharing policy that provides a fair outcome for the operators. Our results highlight the potential energy efficiency gains in the network along with different ways of sharing the cost of the deployed SCs.

Wireless Body Area Networks (WBANs) are composed of various sensors that either monitor and transmit real time vital signals or act as relays that forward the received data packets to a nearby Body Node Coordinator (BNC). The design of an accurate and energy efficient wireless telemonitoring system can be achieved by: i) minimizing the amount of data that should be transmitted for an accurate reconstruction at the BNC, and ii) increasing the robustness of the telemonitoring system to link failures due to the nature of wireless medium. To this end, we present a novel Compressed Sensing (CS) based telemonitoring scheme, called Cooperative Compressed Sensing (CCS), that exploits the benefits of Random Linear Network Coding (RLNC) along with key characteristics of the transmitted biosignals in order to achieve an energy efficient signal reconstruction at the BNC. Simulation studies, carried out with real electrocardiographic (ECG) data, show the benefits of: i) employing RLNC, compared to the case where relays simply store and forward the original data packets, and ii) applying the proposed CCS scheme, compared to traditional CS recovery approaches.

In the next few years, small cells (SCs) are expected to be densely deployed to achieve sustainable capacity enhancement. Due to the high SC density, some SCs will not have a direct connection to the core network, and thus will forward their traffic to their neighboring SCs through a multi-hop backhaul (BH). In such multi-hop architectures, the user association problem becomes challenging with BH energy consumption playing a key role. In parallel, the ever-increasing need to minimize the user equipment (UE) transmission power along with the uplink (UL) and downlink (DL) traffic asymmetry, predicate the joint study of UL and DL. Thus, in this paper, we study the joint UL and DL cell selection problem aiming at maximizing the total network energy efficiency, without compromising the UE quality of service. The problem is formulated as an optimization problem, which is NP-hard. Therefore, we propose a heuristic context-aware algorithm that associates the UEs in an energy-efficient way, while considering both access and BH energy consumption in UL and DL. We evaluate the proposed algorithm performance and we show that it can achieve significantly higher energy efficiency than the reference approaches, while maintaining high spectral efficiency and low UE power consumption.

Mobile data offloading has been proposed as a solution for network congestion. However, the majority of the state-of-the-art is focused on the downlink offloading, while the change of mobile user habits, like mobile content creation and uploading, makes uplink offloading a rising issue. In this work we focus on the uplink offloading using Ip Flow Mobility (IFOM). IFOM allows a LTE mobile User Equipment (UE) to maintain two concurrent data streams, one through LTE and the other through WiFi access technology, that presents uplink limitations due to the inherent fairness design of IEEE 802.11 DCF. In this paper, we propose two uplink offloading algorithms to improve the energy efficiency of the UEs and to increase the offloaded data volume under the concurrent use of access technologies that IFOM provides. In the first algorithm, UEs with heavy traffic are promoted and are given priority in accessing the WiFi Access Point (AP) to offload their data. In the second algorithm, we propose a proportionally fair bandwidth allocation over the data volume needs of the UEs. We theoretically analyse the proposed algorithms and evaluate their performance through simulations. We compare their performance with the 802.11 DCF access scheme and with a state of the art access algorithm under different number of offloading UEs. Through the provided evaluation we show that there is room for improvement in the uplink access scheme of the WiFi that affects the energy efficiency of a UE during IFOM uplink offloading.

Random dense deployment of heterogeneous networks (HetNets), consisting of macro base stations (BS) and small cells (SC), can provide higher quality of service (QoS) while increasing the energy efficiency of the cellular network. In addition, it is possible to achieve lower deployment cost and, therefore, maximize the benefits for the network providers. In this paper, we propose a novel method to determine the minimum deployment cost of a two-tier heterogeneous cellular network using random deployment. After deriving the coverage probability of the two-tier deployment by using stochastic geometry tools, we identify the tier intensities that provide the minimum deployment cost for a given coverage probability. Extensive simulations verify the existence of a unique set of intensities for different coverage constraints.

To meet the ever-increasing traffic demands, future cellular networks are about to include a plethora of small cells (SCs), with user equipments (UEs) being able of communicating via multiple bands. Given that SCs are expected to be eventually as close as 50 m apart, some of them will not have a direct connection to the core network, and thus will forward their traffic to the neighboring SCs until they reach it. In such architectures, the user association problem becomes challenging with backhaul (BH) energy consumption playing a key role. Thus, in this paper, we study the user association problem aiming at maximizing the network energy efficiency. The problem is formulated as an optimization problem, which is NP-hard. Therefore, we propose a cognitive heuristic algorithm that exploits context-aware information (i.e., UE measurements and requirements, the HetNet architecture knowledge and the available spectrum resources of each base station (BS)) to associate the UEs in an energy-efficient way, while considering both the access and the BH energy consumption. We evaluate the performance of the proposed algorithm under two study-case scenarios and we prove that it achieves significantly higher energy efficiency than the reference algorithms, while maintaining high spectral efficiency.

Machine-to-Machine (M2M) area networks must provide connectivity between an M2M gateway and a large number of energy-constrained M2M devices. Attaining high energy efficiency is essential in order to prolong devices lifetime. In this paper, we consider a wireless M2M area network composed of hundreds or even thousands of dormant devices that wake up periodically to transmit data upon request from a gateway. We theoretically analyze the energy efficiency of a Medium Access Control (MAC) protocol that uses a tree-splitting algorithm to resolve the collisions among devices: the Distributed Queuing (DQ) access. Computer-based simulations have been carried out to validate the accuracy of the analytical model and to evaluate and compare the energy consumption of devices using also a basic Contention Tree Algorithm (CTA) and Frame Slotted-ALOHA (FSA). Results show that DQ can reduce energy consumption in more than 35% with respect to CTA and in more than 80% with respect to FSA in dense M2M area networks with devices in compliance with the IEEE 802.15.4 physical layer.

In this paper, a novel Network Coding (NC)-aided Medium Access Control (MAC) protocol with mobility support (NCMOB-MAC) is presented. The proposed protocol is compatible with Automatic Repeat reQuest (ARQ) techniques and can be applied in Vehicular Ad hoc Networks (VANETs). NCMOB-MAC proposes a new way of coordinating the communication between a sender, a moving destination and a set of fixed relay nodes. The relays employ different Contention Window (CW) sizes to assign priorities and optimize the NC opportunities. Extensive simulations have been carried out to evaluate the performance of the protocol and the results show an improvement in throughput and energy efficiency compared to conventional NC-aided MAC protocols.

The IEEE 802.11 Distributed Coordination Function (DCF) is the fundamental access method providing asynchronous best-effort services in Wireless Local Area Networks (WLAN). In this standard, the currently employed Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) and the Binary Exponential Backoff (BEB) mechanism represent major sources of energy consumption at both the access point and mobile stations of a WLAN. To improve energy efficiency in WLANs, this paper introduces an enhanced DCF protocol incorporating bidirectional transmissions in combination with sleep periods, called Bidirectional Sleep DCF (BDSL-DCF). By following this new scheme, every successfully established connection between a sender and its intended destination can be used to exchange data, hence reducing control overhead and channel contention. Furthermore, this functionality allows those mobile stations not participating in data transmission to activate the sleep mode to conserve energy. Simulation results show that BDSL-DCF can outperform DCF in terms of energy efficiency and throughput, with negligible impact on packet transmission delay.

Life expectancy is projected to increase significantly in the coming years. This fact has pushed the need for designing new and more pervasive healthcare systems. In this field, distributed and networked embedded systems, such as Wireless Sensor Networks (WSNs), are the most suitable technology to achieve continuous monitoring of aged people for their own safety, without affecting their daily activities. This paper proposes recent advancements in this field by introducing WSN4QoL, a Marie Curie project which involves academic and industrial partners from three EU countries. The project aims to propose new WSN-based technologies to meet the specific requirements of pervasive healthcare applications. In particular, in this paper, a Network Coding (NC) mechanism and a distributed localization solution are presented. They have been implemented on WSN testbeds to achieve efficiency in the communications and to enable indoor people tracking. Preliminary results in a real environment show good system performance that meet our expectations.

The emerging increase of the number of Base Stations causes redundant energy consumption, especially during low traffic periods, when the Base Stations capacity is underutilized. In this paper, we study energy efficiency issues in multi-operator mobile networks. Our primary goal is to save energy, without compromising the offered Quality of Service, by switching off the excessive Base Stations. To this end, we propose a novel game theoretic strategy using cost-based functions to decide the best suitable Base Stations to remain active. Mathematical analysis and simulations demonstrate that the proposed scheme can significantly reduce the energy consumption.

In this paper we evaluate the energy efficiency of MIMO technologies introduced in the emerging IEEE 802.11n standard for infrastructure based WLANs. The main focus is on exploiting multiuser capabilities of MIMO technologies, while studying the proper design of multiuser MAC schemes to achieve an energy efficient solution. Three different multiuser MAC schemes are presented and analyzed. Analytical models for energy efficiency are mathematically developed and verified with link-level computer simulations. The results show the feasibility of achieving higher energy efficiency with the proper adjustment of the system parameters, and without significant degradation of throughput performance.

Attaining very high energy efficiency is one of the big challenges to implement Machine-to-Machine (M2M) networks whose lifetime (without human intervention) must be measured in years. In this paper, we consider a synchronized duty-cycled M2M network composed of a large number of devices that periodically wake up their radio interfaces to transmit data to a coordinator. We theoretically analyze the delay and energy efficiency of two contention-based Medium Access Control (MAC) protocols for this kind of networks. One protocol is based on Frame Slotted ALOHA, and the other is based on a tree-splitting contention resolution algorithm. Computer-based simulations have been carried out to ensure the accuracy of the theoretical models and to evaluate and compare the performance of the two alternatives for M2M applications based on low power Wi-Fi devices.

In this paper, we evaluate a novel contention-aware channel selection algorithm that focuses on energy efficiency improvement of a secondary network (SN) in a scenario where other non-cooperating SNs are also using the primary resources. We present a detailed energy efficiency analysis and we study how the time between two consecutive sensing periods affects the energy efficiency. Our analysis proves that a categorization of the idle channels based on their contention level and the selection of the less contended ones can result in up to 70% gain in energy efficiency. The model is further evaluated through simulations.

In this paper, we exploit the characteristics of physical layer network coding (PNC) in multicast short range communication (SRC) networks. We present a scalable scenario of partially overlapping SRC networks, where collisions are resolved through indirect inter-group cooperation based on the features of PNC. Our scenario consists of a central network and several peripheral networks. In our previous work we proved that the central network presents significant gains in terms of throughput, delay and energy efficiency when applying the proposed scheme. Here we explore the impact of that scenario on the peripheral networks through a decomposition approach and we prove that they also present significant performance gains.

Reducing the energy consumption in wireless networks has become a significant problem, not only because of its great impact on the global energy crisis, but also because it represents a noteworthy cost for telecommunication operators. The Base Stations (BSs), constituting the main component of wireless infrastructure, are intended to serve their customers during peak time periods. On the other hand, they are more than sufficient when the traffic load is low. Our paper proposes a solution for the problem of inefficient use by using a dynamic BSs switch on/off algorithm. We demonstrate via analysis and simulations that we can achieve significant reduction in energy consumption when we dynamically switch off the unnecessary BSs depending on the traffic variations and the distance between the User Equipments (UEs) and their associated BS. While maintaining the Quality of Service (QoS), we calculate the maximum number of BSs that can be switched off considering the time varying characteristic of the traffic pattern.

The design of communications protocols that exploit the availability of both cellular and short-range radio access interfaces in a same terminal can be exploited to improve the energy efficiency of wireless communications networks. Devices equipped with a cellular radio interface can act as dynamic gateways to provide energy-constrained devices in its single-hop cluster with cellular connectivity. For this purpose, any device may discover its single-hop neighbourhood in order to select the appropriate gateway candidates. Conventional neighbour discovery algorithms have a great cost in terms of delay and energy consumption, and thus they are not the optimal approach for energy-constrained devices. This paper presents the energy consumption analysis of two distributed neighbour discovery algorithms based on frame slotted-ALOHA, and evaluates their performance in terms of energy consumption. In addition, it describes the conditions that minimize the energy consumption in the discovery process.

The Persistent Relay Carrier Sensing Multiple Access (PRCSMA) Protocol has been proposed in the literature as a Medium Access Control (MAC) protocol suitable for Cooperative Automatic Retransmission Request (C-ARQ) schemes. The improvement in throughput achieved with PRCSMA is already known. In this paper, we analyze the energy efficiency of this protocol to assess application to energy-constrained networks. Towards this aim, a suitable energy model is derived. The model has been validated through computer simulations and shows that a C-ARQ based on PRCSMA can help improve the energy efficiency of wireless communications and thus increase the lifetime of devices.

In this paper we show how a cooperative Medium Access Control (MAC) protocol can help extend the lifetime of Machine to Machine (M2M) networks. A comparison between non-cooperative Automatic Repeat reQuest (ARQ) schemes (retransmissions performed only from the source) and a cooperative retransmission scheme (all the stations in the network are spontaneous helpers and assist the destination during the communication) in energy-constrained networks is also presented in this work. The results shown in this paper are discussed in terms of the trade off between the network lifetime and the amount of data delivered, leading to the conditions where it is possible to optimize the lifetime of this kind of networks.

In this paper, we propose a switch on/off algorithm for Base Stations (BSs), which exploits the knowledge of the distance between the User Equipments (UEs) and their associated BS. Our novel approach hopes to provide an improvement to the problem of energy consumption. The major concern lies on reducing the energy consumption of the telecommunication networks by optimizing the power utilization without sacrificing the offered Quality of Service (QoS). Our proposed scheme achieves a significant power saving, based on switching off the Base Stations that are underutilized during low traffic periods (especially during night) in the LTE-Advanced.

Mobile Machine-to-Machine (M2M) market is expected to grow dramatically in the upcoming years; predictions agree that the majority of wireless traffic will correspond to this type of communication. M2M devices deployed in proximity to each other might be handled as groups or clusters when sharing the same communication attributes and serving to achieve joint target. Moreover, devices that feature multiple radio interfaces are commonly used nowadays; they can be connected to a cellular access network, e.g., LTE, and simultaneously to a short-range network, also known as capillary network, among surrounding devices, e.g., Wi-Fi and ZigBee. For services such as over-the-air (OTA) firmware update, the same information shall be sent to all the group members over the cellular access network. A Multi-Radio Cooperative Retransmission Scheme for Reliable Multicast Services is presented as a solution to reliably manage reception errors occurred over the cellular network; by carrying out retransmissions over a short-range network it is possible to reduce both the traffic load over the cellular link and the energy consumption in error recovery. Ns-3 simulations were performed with LTE network models to analyze the scheme in terms of energy consumption and prove its usefulness in autonomous, battery driven, devices.

This paper studies the feasibility of using low-power wireless technologies such as Bluetooth, IEEE 802.15.4 and ZigBee in high-speed railway scenarios that involve bidirectional ground-to-train communication. The presented results have been obtained through experimental tests conducted at the Madrid-Barcelona high-speed rail line. A multiplatform communication system has been installed in a high-speed train, circulating at velocities up to 300 km/h, whereas autonomous devices have been disseminated along of the railway path to communicate with the onboard devices. The conclusions drawn from this work will be used as guidelines for the future implementation of autonomous communication platforms for high-speed rail connectivity.

We demonstrate for the first time an analytical model for computing the saturation throughput of a Medium-Transparent MAC protocol in 60 GHz Radio-over-Fiber networks, assuming a finite number of terminals and ideal channel conditions. The model takes into account contention both at the optical and the wireless layer, effectively incorporating the Medium-Transparent MAC mechanism for seamless and dynamic capacity allocation over both optical and wireless transmission media. Based on this model, we provide an extensive saturation throughput performance analysis of the Medium Transparent MAC protocol for various optical capacity availability scenarios and different numbers of wireless users. The theoretical results are found to be in good agreement with respective simulation-based findings, confirming that the employment of Medium Transparent MAC protocols can allow for efficient extended LAN operation of 60 Radio-over-Fiber networks.

Accurate representation of the physical layer is instrumental for a sound design and optimization of Medium Access Control (MAC) protocols for cooperative wireless networks. However, the vast majority of MAC protocols are designed and analyzed by considering simplified physical layer and channel models, which often lead to too optimistic performance predictions. In particular, even though many experimental activities have showcased the important role played by shadow-fading, most protocols are designed and evaluated by taking into account only the transmission distance (circular coverage model) or only the fast-fading. Motivated by the proved unsuitability of these models, the contribution of this paper is threefold: i) we provide important considerations on how to adequately include the effect of shadowing into the design of MAC protocols for cooperative networks; ii) we provide an analytical framework to determine the subset of active relays in order to meet a given Quality-of- Service (QoS) requirement; and iii) we study, through analysis and simulation, the performance of a promising MAC protocol for cooperative networks, which is called Persistent Relay Carrier Sensing Multiple Access (PRCSMA), by explicitly taking into account the effect of shadowing. Our study shows that shadowing can dramatically change system and protocol performance.

We present in this paper the evaluation of the energy consumption of PRCSMA, an 802.11-based medium access control protocol designed to coordinate the retransmissions from the relays in a wireless network implementing a Cooperative Automatic Retransmission Request (C-ARQ) scheme. A comparison in terms of energy efficiency with non-cooperative ARQ schemes (retransmissions performed only from the source) and with ideal C-ARQ (with perfect scheduling among the relays) is included in this paper. The main results show the conditions under which a C-ARQ scheme with PRCSMA outperforms, in terms of energy efficiency, non-cooperative ARQ schemes and also show that the overhead of the MAC layer cannot be neglected in order to accurately evaluate the performance of a C-ARQ scheme.

In this paper, we describe GREENET (an early stage training network in enabling technologies for green radio), which is a new project recently funded by the European Commission under the auspices of the 2010 Marie Curie People Programme. Through the recruitment and personalized training of 17 Early Stage Researchers (ESRs), in GREENET we are committed to the development of new disruptive technologies to address all aspects of energy efficiency in wireless networks, from the user devices to the core network infrastructure, along with the ways the devices and equipment interact with one another. Novel techniques at the physical, link, and network layers to reduce the energy consumption and carbon footprint of 4G devices will be investigated, such as Spatial Modulation (SM) for Multiple-Input-Multiple-Output (MIMO) systems, Cooperative Automatic Repeat reQuest (C-ARQ) protocols, and Network Coding (NC) for lossy networks. Furthermore, cooperation and cognition paradigms will be exploited as additional assets to improve the energy efficiency of wireless networks with the challenging but indispensable constraint of optimizing the system capacity without degrading the user's Quality-of-Service (QoS).

The emerging 802.11n standard establishes the integration of MIMO technology in WLANs with the goal of achieving high data rates. However there are still many open issues regarding MAC protocol design for MIMO based systems, especially in order to exploit the multiuser capabilities of the MIMO channel. In this paper we propose a novel MAC scheme that considers an opportunistic channel-aware scheduling policy to achieve simultaneous downlink transmissions to multiple users. In an effort to offer a complete and practicable proposal, our MAC scheme is combined with a low-complexity beamforming technique at the Physical layer in a system where multiple antennas are employed at least at the transmitter side (Access Point). A mathematical model for the throughput performance of the proposed scheme is presented and validated through link-layer simulation results.

In this paper we analyze the performance of a distributed queuing medium access control (MAC) protocol designed to execute cooperative ARQ (C-ARQ) schemes at the MAC layer. Due to the broadcast nature of the wireless channel, a user that receives a data packet with unrecoverable errors can request retransmission from any of the other users in the transmission range of the transmitter that overheard the original transmission. These users can act as spontaneous relays and provide the communication with cooperative diversity gains. Upon retransmission request, the relays have to contend for the access to the channel. The DQCOOP protocol has been proposed in the literature as a high-performance MAC protocol for this kind of scenario. In this paper we theoretically evaluate its performance. The analytical results are supported by computer-based simulation that show the accuracy of the analysis.

We describe in this paper a methodology to facilitate the coexistence of the Distributed Queuing Medium Access Control (MAC) protocol for Ad hoc Networks (DQMAN) with the IEEE 802.11 Standard MAC protocol. By using dual terminals which can operate with the two MAC protocols, it is possible to run a hybrid network with legacy and novel terminals. In addition, it is possible to enable the intercommunication between all the terminals of the network. Computer simulations have been carried out to assess the performance and the feasibility of such dual operation. The main conclusion of the study is that the use of dual terminals allows the integration of DQMAN within legacy networks without degrading the performance of IEEE 802.11 terminals. In addition, the mechanism presented in this paper can be used to enable the coexistence of any cluster-based distributed MAC protocol within IEEE 802.11 networks.

The recently approved 802.11n standard establishes the integration of MIMO technology in WLANs with the goal of achieving high data rates. However, it does not exploit the multiuser capabilities of the MIMO channel. In this paper we present a multiuser downlink transmission scheme that combines low-complexity beamforming at the Physical layer with an opportunistic channel-aware MAC scheduling policy. A mathematical model for the throughput calculation of the proposed scheme is presented and validated through link-layer simulation results.

We present in this paper the analysis of an IEEE 802.11 network in the presence of hidden and exposed terminals when a Cooperative ARQ (C-ARQ) scheme is executed at the MAC layer. When spontaneous helpers transmit to assist in a failed transmission, the area exposed to the original transmission increases in comparison to non-cooperative ARQ schemes. In this paper we quantify this effect and we evaluate the relevance of designing efficient protocols to combat the exposed terminal problem.

The emerging 802.11n standard establishes the integration of MIMO technology in WLANs with the goal of achieving high data rates. However there are still many open issues regarding MAC protocol design for MIMO based systems, especially in order to exploit the multiuser capabilities of the MIMO channel. In this paper we investigate practical solutions to implement multiuser downlink transmission in infrastructure 802.11n based WLANs. A low-complexity beamforming transmission technique is employed at the physical layer and four MAC schemes that vary in complexity and efficiency are presented and evaluated through computer simulations.

We present in this paper the analytical evaluation of a simple mechanism to reduce the average transmission delay of master stations in a network based on the Distributed Queuing MAC protocol for Ad hoc Networks (DQMAN). When DQMAN is executed, the network is self-organized into dynamic and spontaneous master-slave clusters. Within each cluster, a high performance MAC protocol based on a tree-splitting collision resolution algorithm which uses access minislots is executed. By allowing temporary master stations to avoid contention to get access to the channel, their average packet transmission delay can be effectively reduced compared to that of slaves. This technique provides thus master stations with higher access priority to the channel and, indeed, could be used in any MAC protocol based on access minislots to provide a subset of users with higher priority.

In this paper we describe a new MAC protocol for ad hoc networks called distributed point coordination function (DPCF). It constitutes an extension of the PCF of the IEEE 802.11 standard to operate over infrastructureless networks. It combines both the operation of DCF and PCF. Users get access to the channel through the DCF function. However, once they get access to the channel, they establish a virtual cluster where the PCF coordination function can be executed. The performance of DPCF in single-hop and multi-hop ad hoc networks has been evaluated by means of link-level computer simulation. The results show that DPCF outperforms DCF in terms of throughput and average transmission delay when executed in networks without infrastructure.

Body sensors consume a significant amount of power when data is either transmitted or received. This paper evaluates the energy efficiency per utile bit as a function of the network load and data frame length while introducing power management solutions for a high-performance distributed queuing medium access control (DQ MAC) protocol in wireless body sensor networks. To do so, a new energy analytical model derived from delay theoretical studies is provided. Simulation results are displayed to further validate the protocol energy performance using IEEE 802.15.4 system parameters. The achieved outcome shows that the proposed scheme outperforms IEEEperformance using IEEE 802.15.4 system parameters. The achieved outcome shows that the proposed scheme outperforms IEEE 802.15.4 MAC in all possible scenarios.

Wireless body sensor networks (BSNs) in healthcare systems operate under conflicting requirements. These are the maintenance of the desired reliability and message latency of data transmissions, while simultaneously maximizing battery lifetime of individual body sensors. In doing so, the characteristics of the entire system, including physical, medium access control (MAC), and application layers have to be considered. The aim of this paper is to develop a new MAC model for BSNs to fulfill all these specific rigorous requirements under realistic medical settings. For that purpose, a novel cross-layer fuzzy-rule scheduling algorithm and energy-aware radio activation policies are introduced. The main idea is to integrate a fuzzy-logic system in each body sensor to deal with multiple cross-layer input variables of diverse nature in an independent manner. By being autonomously aware of their current condition, body sensors are able to demand a "collision-free" time slot, whenever they consider it strictly required (e.g. high system packet delay or low body sensor residual battery lifetime). Similarly, they may refuse to transmit, if there is a bad channel link, thus permitting another body sensor to do so. This results in improving the system overall performance. The proposed MAC model is evaluated by computer simulations in terms of quality of service and energy consumption under specific healthcare scenarios.

The Persistent Relay Carrier Sensing Multiple Access (PRCSMA) has been recently presented in the literature as a novel Medium Access Control (MAC) protocol based on the IEEE 802.11 and modified to cope with the contention among the relays in a Cooperative ARQ (C-ARQ) scheme. We present in this paper a theoretical model to calculate the average cooperation delay of PRCSMA. Computer simulations have been carried out to assess the accuracy of the model.

DQCA is a near-optimum medium access control (MAC) protocol designed for wireless local access networks (WLANs). The protocol operates as a random access scheme under low traffic load and switches smoothly and automatically to a reservation scheme as the traffic grows. The inherent feedback mechanism of DQCA facilitates the implementation of a link adaptation algorithm that properly selects the best transmission rate taking into account the state of the wireless channel. This paper presents an analytical model for the evaluation of the performance in terms of throughput and mean message delay in the presence of a time-variant channel response.

A throughput analysis of the Persistent Relay Carrier Sensing Multiple Access (PRCSMA) protocol is presented in this paper. The protocol has been designed to execute a cooperative ARQ (C-ARQ) scheme in wireless networks. The model herein presented takes into account the contention time among the relays. This time consists in wasted time due to both backoff deferral periods and collisions occurred between relays attempting to access the channel in a same time slot. Link-level computer simulations have been carried out to assess the accuracy of the model and to evaluate the performance of the protocol.

Several clustering algorithms have been proposed during the last decade within the context of ad hoc and sensor networks. They allow adding some organization to an otherwise disorganized network. Although the virtual organization attained by clustering has been typically designed within the scope of routing algorithms, clusters can also enable the use of conventional highly efficient medium access control (MAC) protocols to support heavy traffic loads. In this paper we adopt a novel approach to calculate the saturation throughput of a single- hop ad hoc network when using a MAC protocol embedded in a passive clustering mechanism based on the Carrier Sensing Multiple Access (CSMA) protocol. The DQMAN protocol is considered as a study case to validate the proposal.

The distributed queuing MAC protocol for cooperative networks (DQCOOP) is presented in this paper as an innovative MAC protocol designed to coordinate the relay retransmissions in a cooperative automatic retransmission request (C-ARQ) scheme for wireless networks. The distributed cooperative ARQ scheme when the DQCOOP is applied at layer two is compared to an ideal non-cooperative ARQ scheme. Computer simulations show that the relay multiple access problem is efficiently handled by the DQCOOP and the cooperative approach outperforms the traditional non-cooperative ARQ scheme in all cases. In addition, the DQCOOP is compared with an IEEE 802.11-based MAC protocol for C-ARQ schemes, demonstrating improved efficiency.

Voice transmission over WLAN and cross-layer optimization are emerging research topics. This paper proposes two novel cross-layer mechanisms for a WLAN system where the offered traffic is of mixed nature (voice and data) while using a distributed MAC protocol. On one hand, the performance of the proposed mechanisms has been analyzed, and a significant system efficiency improvement in terms of throughput and packet delay for data nodes is shown. On the other hand, a remarkable increase in the number of simultaneous possible voice nodes is also achieved. These benefits are obtained by means of a PHY-MAC dialogue and a smart scheduling of the radio resources. Transmissions are scheduled taking into account the measurements of the channel state and the waiting time of packets in the accessing system. The two proposed mechanisms have different performance behavior as they present a trade-off between system enhancement and fairness in resource assignment among the nodes. The obtained results emphasize the advantages of the proposed schemes and the importance of Cross-Layer design in wireless communication systems.

We consider a cooperative network where the communication between a single source-destination pair is assisted by the transmission of relays. In the considered cooperative model, once a node requires cooperation, it broadcasts a claim for cooperation message. Under high mobility conditions or in some special scenarios this is the natural procedure to discover the potential relays. However, when there is a large number of nodes that can potentially serve as a relay, a Multiple Relay Access Control (MRAC) problem turns up and the relay transmissions must be organized in an effective manner. We introduce this problematic and propose three different strategies to manage this severe competitive channel. In these strategies either the source, the destination or both trigger the cooperative process. The methodology employed makes the results and conclusions valid for a wide range of cooperative scenarios, and hence, useful for a wide range of applications.

Cross-layer opportunistic scheduling on DQCA-based WLAN systems yields high performance results. This paper emphasizes the need for accurate channel state information (CSI) and presents an enhanced mechanism that provides frequent CSI updates. The proposed idea consists in introducing special update frames specifically dedicated to channel state estimation. The impact of this mechanism on the performance of the system is evaluated through simulations. The paper shows that there is a trade-off between the overall system performance and the number of update frames that are used. The periodicity of these special frames is a parameter that needs to be carefully selected, depending on the channel time-variation characteristics.

Significant power is consumed at a sensor node when it either transmits a packet or when it receives a packet. In this paper, we study energy efficiency as a function of the number of sensors in the network and the payload length. Additionally, we propose power management solutions based on a distributed queuing MAC protocol for wireless sensor networks. Analytical values for the energy consumption performance are derived as a function of the system parameters. The obtained results show that our proposed MAC scheme outperforms that of IEEE 802.15.4. These benefits are obtained from eliminating back-off periods and collisions in data packet transmissions while minimizing the control overhead and the overall energy consumption

This paper addresses the analysis of WCDMA systems with repeaters deployment. A generic and compact expression for up- and downlinks evaluation has been mathematically derived so that transmission powers and other radio resource management parameters can be calculated without simplifications. In particular, the real different path delays, taking into account the repeaters presence and the finite nature of the time window of Rake receivers are considered. This allows an enhanced analysis with respect to classical approaches from a system level viewpoint. Furthermore, higher reliable and accurate predictions on network performance can be obtained, which can be remarkably useful for network planning and management. By using these expressions, relevant network parameters have been evaluated and compared with the ones obtained using the classical approximations. The differences in the obtained metrics are highlighted, putting in evidence the improvement provided by the proposed analysis.

It has been shown that the cooperation among nodes can improve the performance of a network under certain considerations. So far, research focus has been mainly put on cooperation and not on the coordination required to obtain this cooperation. In this paper we discuss how the MAC layer plays a key role in determining the effectiveness of a cooperative orthogonal multiple relay channel. We propose and analyze the performance of a novel MAC protocol based on the legacy IEEE 802.11 standard in a representative and general study case scenario. The main conclusion of the study is that a proper selection of the MAC protocol being used in a cooperative system is highly relevant in order to actually achieve the benefits of this kind of systems

This paper addresses the analysis of WCDMA systems with repeaters deployment. The real different path delays, taking into account the repeaters presence and the finite nature of the time window of Rake receivers are considered. This allows an enhanced analysis with respect to classical approaches from a system level viewpoint. Results show that not taking into account these effects imply erroneous metrics. Indeed, some of the most relevant parameters in network performance evaluation are clearly affected

Cross-Layer optimization is an emerging research topic. This paper proposes two novel cross-layer mechanisms to be included in a WLAN system where a near-optimum distributed MAC protocol is used. Their performance in terms of throughput and packet delay is analysed, and a significant system efficiency improvement is shown. This benefit is achieved by means of a PHY-MAC dialogue and a smart scheduling of the radio resources. Transmissions are scheduled taking into account the measurements of the channel state and the waiting time of packets in the accessing system. The two proposed mechanisms have different performance behaviour and thus present a trade-off between system enhancement and fairness. The obtained results emphasize the advantages of the proposed schemes and the importance of cross-layer design in wireless communication systems

This paper proposes a cross-layer priority-based scheduling algorithm for WLAN systems using the DQCA MAC protocol where heterogeneous voice-data traffic is present. In this algorithm voice users have always the highest priority while among the data users, higher priority is given to the user with higher measured signal-to-noise ratio. Therefore, each user transmits with the maximum corresponding available rate. The performance of the proposed algorithm is compared to those without cross-layer and with the basic DQCA operation without any service distinction. Simulation results show that this enhanced scheme improves the efficiency of the system in terms of data throughput and voice users' capacity. Furthermore, for a given number of voice users, a higher offered data load is supported

This paper proposes and analyses a novel MAC protocol for wireless ad hoc networks that makes use of distributed queues to achieve an efficient use of the radio channel. The protocol includes a dynamic self-configurable master-slave architecture that allows the synchronism between the nodes of the network. Computer simulations demonstrate that the proposed scheme outperforms throughput bounds achieved when using a legacy 802.11 MAC protocol for mobile ad hoc networks.

This paper presents and analyzes a new near-optimum medium access control (MAC) protocol. The proposed access scheme is suitable for a CDMA mobile communication environment, and keeps under control and upper bounded the number of simultaneous transmissions. It has a delay performance approaching that of an ideal optimum M/M/K system, where K is the number of spreading codes being used (maximum number of simultaneous transmissions). The protocol is a free random access protocol when the traffic load is light, and switches smoothly and automatically to a reservation protocol when traffic load becomes heavier. It is based on distributed queues and a collision resolution algorithm. Moreover, a physical receiver structure is proposed and analyzed in order to preserve the robustness of the protocol in a wireless link. The results obtained show that the protocol outperforms other well known medium access protocols in terms of stability and delay, even when taking into account the loss caused by channel propagation conditions.