Multiple solutions for the coexistence of different radio access technologies operating in the same frequency band have been proposed for 5G and WiFi. Most solutions based on spatial division just consider a small amount of radio access points, one link direction, and/or a single radio access technology. As a consequence, the performance of these solutions on realistic wireless network deployments may be poor and difficult to estimate. This paper investigates the serving of multiple users by multiple radio access technologies with the objective of minimizing the interference among network nodes. This is done by jointly optimizing the beams and link directions as well as the transmission powers, so as to ensure fair and near-optimal throughput allocation over time. For this purpose, a generalized beam-gain model for small-scale antenna arrays is proposed. We evaluate our proposed solution for realistic network scenarios in order to show its effectiveness.

In recent years, owing to the architectural evolution of 6G towards decentralization, distributed intelligence is being studied extensively for 6G network automation. Distributed intelligence, based on Reinforcement Learning (RL), particularly Q-Learning (QL), has been proposed as a potential direction. The distributed framework consists of independent QL agents, attempting to reach their own individual objectives. The agents need to learn using a sufficient number of training steps before they converge to the optimal performance. After convergence, they can take reliable management actions. However, the scalability of QL could be severely hindered, particularly in the convergence time - when the number of QL agents increases. To overcome the scalability issue of QL, in this paper, we explore the potentials of the Deep Q-Network (DQN) algorithm, a function approximation-based method. Results show that DQN outperforms QL by at least 37% in terms of convergence time. In addition, we highlight that DQN is prone to divergence, which, if solved, could rapidly advance distributed intelligence for 6G.

Network edge environments like in-flight or in-train communications utilize satellite-terrestrial integrated networks. These networks however suffer from limited backhaul and cache resources, leading to sustainability issues due to increasing traffic demands. The problem becomes more challenging for 5G ecosystems, where applications have distinct requirements, rendering the management and orchestration of conventional satellite-terrestrial networks harder. Therefore, software-defined networking and edge network slicing are envisioned to enhance resource management and increase flexibility of resource allocation. However, the complexity of management and orchestration increases in cases where service providers, allocated to a slice, do not share information about their users with the infrastructure providers, due to privacy or other concerns. To incorporate the aspect of slice collaboration, we define network slices with respect to their willingness of sharing user traffic statistics with the infrastructure provider. Taking in-flight entertainment and connectivity services (IFECS) as an interesting 5G use-case, we introduce a system model mimicking the practical deployment of slicing for aircrafts using satellites. We propose a mixed integer non linear program that aims at maximizing the number of slices served. Utilizing our model we evaluate the deployment cost of slices with respect to cache and backhaul resources. Our results show that uncooperative slices have a lower selection probability. Nonetheless, we demonstrate that if the slice cost is paid by slice owners, uncooperative slices increase their chances of being served by 33%. Overall, cooperative slicing can revolutionize the IFECS system as it accommodates 200% more slices compared to uncooperative slicing.

Next-generation networks are expected to provide higher data rates and ultra-low latency in support of demanding applications, such as virtual and augmented reality, robots and drones, etc. To meet these stringent requirements of applications, edge computing constitutes a central piece of the solution architecture wherein functional components of an application can be deployed over the edge network to reduce bandwidth demand over the core network while providing ultra-low latency communication to users. In this article, we provide solutions to resource orchestration and management for applications over a virtualized client-edge-server infrastructure. We investigate the problem of optimal placement of pipelines of application functions (virtual service chains) and the steering of traffic through them, over a multi-technology edge network model consisting of both wired and wireless millimeter-wave (mmWave) links. This problem is NP-hard. We provide a comprehensive “microscopic” binary integer program to model the system, along with a heuristic that is one order of magnitude faster than optimally solving the problem. Extensive evaluations demonstrate the benefits of orchestrating virtual service chains (by distributing them over the edge network) compared to a baseline “middlebox” approach in terms of overall admissible virtual capacity. Moreover, we observe significant gains when deploying a small number of mmWave links that complement the Wire physical infrastructure in high node density networks.

Network programmability also sneaked into the mobile world leading to the emergence of Software-Defined Radio Access Network (SD-RAN) architectures. Interestingly, while only a small number of prototype architectures exist for SD-RAN, their performance evaluations are unfortunately also limited. Recent evaluations are carried out for small network dimensions of up to 50 devices, while emerging 5G/6G networks envision numbers of devices beyond 5000. Although 5G/6G applications are more stringent with respect to latency guarantees, performance evaluations of such low scale remain questionable. To fill this void, this paper presentsMARC: a novel benchmarking tool for SD-RAN architectures and their controllers. We useMARCto measure, analyze and identify performance implications for two state-of-the-art open source SD-RAN solutions:FlexRANand5G-EmPOWER. We perceive results for monitoring application scenarios considering fully centralized control. For this setting, our findings show that the proposed architectures with a single SD-RAN controller are not scalable and can even lead to unpredictable network operations. Using our tool and based on our insights, we provide and implement design guidelines for the internal working behavior of the existing controllers.

Network slicing is envisioned as a tool for 5G networks to provide network flexibility and isolation among different logical networks. While network slicing is well investigated in the fixed-network side, in the Radio Access Network (RAN) there remain challenging problems, which originate mainly from the stochastic nature of the wireless channels and complex resource coupling between slices. In this work, we investigate a network slicing problem for the downlink RAN of a cellular network. Our target is the reduction of resource usage while guaranteeing slice isolation and simultaneously accounting for each slice's average rate and delay requirements. We tackle the problem with a Lyapunov optimization approach, leading to a simple resource assignment procedure that we can prove to achieve isolation while satisfying all slice guarantees. The proposed procedure leads to a functional split, where resources are scheduled within each slice by a slice manager, while a Software-Defined RAN (SD-RAN) controller dynamically re-assigns resources to each slice. We verify our approach through extensive simulations and provide insight on how to fine-tune available system parameters.

In this article, we experimentally measure the throughput performance of a Wi-Fi, 802.11n, network when it is affected by LTE downlink transmissions. Our practical approach is based on a modular experimental test-bed. We initially compare our measurement results with the case without LTE interference; and further discuss that even the 3GPP features cannot guarantee coexistence in all cases and this might hamper the practicality of mobile technology in the unlicensed radio spectrum. For this reason, we enhance our test-bed introducing the Software-Defined Radio Access Network (SD-RAN) controller 5G-EmPOWER. Thus borrowing from the higher agility of software-defined networking. By using the SD-RAN control to adaptively tune LTE-eNB downlink transmission parameters, we experimentally prove the validity of this approach to improve Wi-Fi network throughput, as well as we shed light onto the new potentials that the SD-RAN controller can lead to automate network optimization.

Among the significant advances in mobile network technology, as evident in the latest 3GPP releases, one of the most notable is the possibility to do aggregation between licensed and unlicensed carriers. With LTE transmitting over unlicensed bands, obvious concerns of a fair co- existence with other preexisting technologies have risen up. In this study, we aim to evaluate the impact of LTE transmission on the key mechanism of Clear Channel Assessment (CCA), which is common to several unlicensed systems, amongst which Wi-Fi is the most notable. Relying on the statistical tool of stochastic geometry and a semianalytical approach, we will obtain the probabilities of Wi-Fi preamble false alarm and detection under a wide set of realistic propagation effects, such as path-loss and Rayleigh distributed fading. Above all, we will model the effect of a single LTE downlink interfering transmission, as well as the aggregate interference effect. Hence, we shall be able to evaluate the modified energy detection threshold that has been long debated between 3GPP and IEEE 802.11 Working Groups.

5G networks will incorporate new innovative technologies and concepts such as network virtualization, SDN/NFV, multi-tenancy and network slicing. Moreover, resource orchestration play a pivotal role to dynamically deploy network services and allocate resources. Orchestration is a control function for resource management in the network core and centralized cloud infrastructure. However, for end-to-end slicing and resource management, the orchestration functions must also be realized at the network edge i.e., the RAN segment. In this paper, we present an architecture for active RAN resource orchestration in which radio resource allocation to different tenants is dynamically scaled in real-time. A parallel can be drawn to the classic spectrum sharing scenarios as we evaluate the well known co-primary sharing model in a multi-tenant RAN context. Moreover, we extend SimuLTE, a well-known system level simulation model to integrate our RAN orchestration architecture and implement different scheduling policies. We evaluate system level network performance using fine-grained radio resource sharing approach and evaluate the involved performance-fairness trade-offs.

An important target for 5G networks is to enable resource sharing among network tenants such as Mobile Virtual Network Operators and Service Providers. Several domains of resource sharing have been considered including infrastructure (compute, storage and networking), transport, Radio Access Network (RAN) and Radio Frequency (RF) spectrum. RAN and spectrum sharing are expected to be an integral part of a multi-tenant 5G network. In this paper, a centralized, fine-grained active RAN and spectrum sharing approach has been presented and analyzed using a modified SimuLTE model. The presented model can be used for analyzing active RAN and spectrum sharing models considered in a multi-tenant 5G network. We present the core modules that enable dynamic allocation of RAN slices with dedicated spectrum and resource scheduling functions. We also present preliminary simulation results that give an insight into the actual benefits and trade-offs of active spectrum sharing among RAN tenants at different time-frequency granularities.

The surge of mobile data traffic forces network operators to cope with capacity shortage. The deployment of small cells in 5G networks shall increase radio access capacity. Mobile edge computing technologies can be used to manage dedicated cache memory at the edge of mobile networks. As a result, data traffic can be confined within the radio access network thus reducing latency, round-trip time and backhaul congestion. Such technique can be used to offer content providers premium connectivity services to enhance the quality of experience of their customers on the move. In this context, cache memory in the mobile edge network becomes a shared resource. We study a competitive caching scheme where contents are stored at a given price set by the mobile network operator. We first formulate a resource allocation problem for a tagged content provider seeking to minimize the expected missed cache rate. The optimal caching policy is derived accounting for popularity of contents, spatial distribution of small cells, and caching strategies of competing content providers. Next, we study a game among content providers in the form of a generalized non-smooth Kelly mechanism with bounded strategy sets and heterogeneous players. Existence and uniqueness of the Nash equilibrium are proved. Finally, numerical results validate and characterize the performance of the system.

The surge of mobile data traffic has spurred academia and industries to begin developing 5G networks. 5G is meant to overcome limitations of 4G cellular technology relying on the dominant trend of mobile network densification with the deployment of small cell base stations. To accelerate this process, low complexity and inexpensive remote radio heads (RRHs) are deployed massively and connected to a centralized pool of resources. In this work, we study the problem of inter-cell interference (ICI) which arises in frequency reuse one multi-tier 5G networks. We entrust the management of RRHs to a software-defined network controller and we take advantage of network functions virtualization. Our contributions consist of proposing Dynamic Strict Fractional Frequency Reuse (DSFFR), a method to relieve ICI which dynamically divides the small cell area in a different number of sectors. Furthermore, we formulate a joint scheduling problem composed of two schedulers which operate at different time granularity to transmit downlink packets. Modeling the coverage area with the tool of stochastic geometry and solving with simulations the joint scheduling problem, we are able to show that DSFFR outperforms the static scheme. Performances are addressed in terms of spectral efficiency and packet blocking probability.

Professional Mobile Radio (PMR) is a niche market which has been recently revitalized. Since public safety officers are required to operate in challenging or extreme conditions, radio communication is an essential asset to enable them to communicate with one another and with command centers organizing operations. We focus on an advanced deployment in which connectivity is provided by a temporary aerial-terrestrial network made of aerial and terrestrial nodes to create 4G LTE-A connectivity and to provision advanced data services in a geographical area of interest. In cases of scarce radio coverage of the aerial platforms, terrestrial nodes can conveniently act as relays to route traffic to/from the serving aerial base stations. We study connectivity and the service interruption time prior to reconnecting to a relay in a network consisting of 4G handhelds and relays. We study connectivity resorting to stochastic geometry, while modeling at the same time the amount of available resources at each relay node and radio signal propagation using the Okumura-Hata model for the urban environment. We will show that a region of space around a relay exists which allows us to optimize connectivity and minimize delay.

In this paper we study 3GPP mobility robustness in the context of Public Safety (PS) communications. In specific, we investigate the scenario in which 4G LTE connectivity is provisioned by means of Aerial evolved Node Bs (AeNBs) mounted on Low Altitude Platforms (LAPs) raised in the sky at an altitude ranging from few hundreds meters to one kilometer. Given the peculiarities of PS communications, the event of handover (HO) is particularly crucial for PS users. It is well understood that a trade-off exists between events of radio link failure (RLF) and HO completion, which is usually achieved by proper tuning of handover parameters. We propose a policy-based HO parameters adjustment in the form of a heuristic, which exploits the information provided by the Mobility Robustness Optimisation (MRO), in order to to achieve such a trade-off. Using simulations, we show that our heuristic solution can achieve the above mentioned trade-off, taking into account the different HO phases and incorporating a suitable Air-to-Ground (ATG) signal propagation model.

The endeavor to develop 5G technology aims to support the recent outstanding mobile data traffic growth. In this regard, mobile network providers will be able to leverage on cloud edge-caching to offer services with enhanced quality of experience on the move. By this technology, dedicated cache space of mobile networks can be provisioned to OTT content providers, e.g., over metropolitan areas covered the network of a mobile network provider. In this work we address the problem of fair pricing such caching service, with storage the actual shared resource for caching. We study a scheme in which contents are dynamically stored in the edge memory. The mobile network provider offers a price λ for storing contents on the shared cache, thus engendering competition for cache memory sharing among content providers. We model such competition among OTT content providers using the economic notion of Kelly mechanism. Hence, we have studied the Stackelberg equilibrium, i.e., the optimal price configuration for the network provider. Numerical results describe the structure of the Nash equilibrium and the optimal prices resulting from the network provider optimal strategy.

Abstract High‐speed train (HST) is revitalizing the train as a preferred mid‐range transportation system. The provision of broadband Internet connectivity onboard trains is one of the key challenges in the competition among train operators. Unprecedented spectral efficiency and data rates (up to 100Mbps in high mobility) of the Universal Mobile Telecommunications System long‐term evolution (LTE) are expected to offer the solution for high‐speed Internet access onboard in HSTs. Massive wireless access and frequent handovers (HOs) of a large number of users might potentially cause service interruptions, and this, in turn, degrades intolerably the quality of experience (QoE) of users' onboard Internet access. In this paper, we propose a solution based on distributed antenna system that combines directional and omni‐directional antennas as train‐to‐ground radio‐access terminals (T‐RATs) and LTE femtocells in each carriage. Directional antennas are deployed at both ends of the HST to provide multi‐cell access by diversifying the HOs over multiple LTE cells. This mechanism virtually elongates the train size by connecting the front and rear carriages' T‐RATs to the faraway eNodeBs and augmenting the number of cells the HST can be simultaneously connected to. An ad hoc distributed load‐balancing mechanism that consists in offloading backlogged packets to the on‐service T‐RATs is mandatorily paired with multi‐cell access scheme to tie up with the request of seamless onboard Internet service at high QoE level. Copyright © 2015 John Wiley & Sons, Ltd.

To cope up with the booming of data traffic and to accommodate new and emerging technologies such as machine-type communications, the 5th Generation (5G) of mobile networks must be empowered with efficient resource allocation schemes that benefit from the adoption of the Software-Defined networking (SDN) paradigm. In radio communications, allocation of resources is tightly connected with interference. In this paper, we revisit the way wireless interference is managed and avoided relying on the SDN paradigm for controlling the network. The SDN approach is exploited to expose the lower layers of the stack (e.g., Physical and Medium Access Control) to the controller and its applications by making system parameters available, such that it is possible to dynamically configure the network in a logically centralized fashion, by means of specifically designed algorithms. The contribution of this work is threefold. First, we show how to adapt the SDN paradigm to mobile networks. Second, we propose the interference graph as an abstraction that can be used to control interference. Last, we formulate a throughput optimization tool that uses the proposed interference graph as an input.

The 4G Evolved Packet Core (EPC) is the pillar of the Long Term Evolution (LTE) mobile networks. Inspired by the current trend of designing distributed and more autonomous systems, we can notice that the complexity of the existing EPC seriously limits this possibility. We principally consider a reshaping of cellular networks in order to move towards virtual-distributed architectures allowing dynamic deployments of commercial/non-commercial, temporary or local networks. In this paper, we present Flexible Management Entity (FME), a distributed entity which leverages on virtualized EPC functionalities in 4G-LTE cellular systems. We highlight several conceptual and engineering trade-offs in realizing such a system.We also analyze the behavior and benefits of FME in various simulation settings that expose the dynamic deployment scenarios for 4G networks.

Past years have witnessed the surge of mobile broadband Internet traffic due to the broad adoption of a number of major technical advances in new wireless technologies and consumer electronics. In this respect, mobile networks have greatly increased their availability to meet the exponentially growing capacity demand of modern mobile applications and services. The upcoming scenario in the near future lays down the possibility of a continuum of communications thanks also to the deployment of so called small cells. Conventional cellular networks and the small cells will form the foundation of this pervasive communication system. Therefore, future wireless systems must carry the necessary scalability and seamless operation to accommodate the users and integrate the macro cells and small cells together. In this work we propose the V-Cell concept and architecture. V-Cell is potentially leading to a paradigm shift when approaching the system designs that allows to overcome most of the limitations of physical layer techniques in conventional wireless networks.

Wireless sensor networks (WSNs) are meant to monitor natural and man-made phenomena, made of simple low cost sensors interconnected via low data rate communication links to survey wide areas. In this paper, we investigate the trade-off arising from spectrum occupation and packet delivery time in professionally installed wide area WSNs (WA-WSNs). We study two types of network topologies, namely star and mesh topologies, based on the recent IEEE 802.15.4k and multi-channel multi-radio IEEE 802.15.4g standards, respectively. We perform extensive packet level simulations of the mesh topology network, while keeping the star network as a benchmark. Our contribution is threefold. First, we address connectivity in the mesh network by deploying additional relay nodes, when necessary, to enable also each node with at least two independent route alternatives. Second, our simulation results show that the mesh topology requires 20% more spectrum to deliver the whole set of sensed data to the traffic sink compared with the star topology network under delivery time constraints. Finally, we show that only 10% of the nodes in the mesh network actually need additional spectrum and multiple radio transceivers to keep the delay bounded by that of the star topology.

In this paper, we investigate scenarios where 4G LTE base stations are mounted on balloons raised in the sky for the provision of cellular connectivity and coverage within an area of few kilometers (e.g., scenarios for emergency communications). In this context, the link between the base stations need to be completed using wireless technologies, thus impacting the performance of the X2 logical interface. We propose the adoption of a wireless backhaul link based on WiFi technology. The main contributions of this paper consist in: modeling the LTE handover over a WiFi link; analyzing the binary exponential backoff with a hands-on one-dimensional Markov Chain including a finite number of packet retries as well as accounting for packets corruption due to Rice fading; and showing the average handover latency and handover preparation failure probability, thus proving that WiFi can meet LTE handover constraints in the majority of the investigated cases.

In past years, ultrawideband technology has attracted great attention from academia and industry for wireless personal area networks and wireless sensor networks. Maintenance of connectivity and exchange of data require an efficient way to manage the devices. Distributed beaconing defined by ECMA-368 is used to manage the network in fully distributed fashion. All the devices must acquire a unique beacon slot, with the beacon period accessed using a slotted Aloha scheme. In this paper, we study the efficiency of distributed beaconing in the presence of k newcomer devices forming a closed system. Efficiency is measured in terms of energy consumption and network setup delay. ECMA-368 defines two distinct phases: extension and contraction. Both phases are analyzed with particular emphasis on the extension phase by means of an absorbing Markov chain model. The main contributions of this paper are: 1) a systematic approach to model distributed beaconing by formulating two equivalent urn occupancy problems of the extension and contraction phases; 2) the use of exponential generating functions to obtain closed-form expressions of the transition probabilities of the absorbing Markov chain; and 3) comparison to computer simulations based on Opnet modeling and with the preexisting literature.

In this paper the capability of a cognitive radio network to discover available frequency channels in the spectrum licensed to a primary user (e.g., digital TV) is analyzed. We rely on cooperative sensing where fusion of individual sensing outcomes is based on the r-out-of-k decision rule. The study is carried out assuming the point of view of a tagged network of cognitive devices that is surrounded by other uncoordinated transmitters competing for accessing the same portion of the spectrum. The contributions of this work are the following. First, the introduction of a three-state model of the wireless channel. Second, modeling the sensing process by means of the general framework provided by urn occupancy problems accessed in non-uniform fashion. Third, the evaluation of the number of available channels in the presence of interference limiting spectrum availability. Finally, the proposal of a cognitive protocol to mitigate the interference. Results are given for a specific case of interest where all networks are supposed ECMA-392 standard compliant.

In this paper we compare impulse-radio ultra wideband (IR-UWB) physical layer related medium access control (MAC) protocols, Slotted Aloha and optional preamble mode six of IEEE 802.15.4-2011, and preamble sense multiple access when the events of false alarm and miss-detection are introduced. Furthermore, a generalized multi-slot channel access scheme is proposed that can, with a proper selection of slots, represent any of the above MAC protocols. As a result of the generalization, an efficiency factor is then proposed, which allows for the protocols to be compared efficiently. At present, the challenge of designing a random access protocol suitable for IR-UWB is however, not completely solved. The generalized multi-slot model and efficiency factor help in determining the optimal number of slots, given certain preamble lengths and channel conditions. While there does not exist a globally optimal solution for all combinations of preamble length and signal-to-noise ratio, this paper shows that dividing the maximum MAC protocol data unit from 4 to 8 equally-sized slots, each with their own preamble, provides the best solution in all but the extreme cases.

Acquisition systems for sub-surface diagnostic (e.g., earthquake monitoring) require large number of sensors (geo-phones or accelerometers) to be deployed outdoor over large areas (tens of sqkm) to measure backscattered wave fields that are collected into a storage/processing unit (sink node). Aggregated data sets are analyzed to obtain an image of the sub-surface, monitor seismic activity, and declare possible alarm conditions. Cable based connectivity is the bottleneck of current systems, in terms of power consumption and degradation in accuracy. Replacing cables with wireless is now becoming attractive to improve the monitoring quality and reduce the probability of false negatives. Strict sampling synchronization constraint over large geographic areas, high precision sensor localization, high data-rate, and low delay are all topics that call for a scalable network system: Multi-Band Ultra Wide-Band radio transmissions (MB-UWB) play a key role as the only viable technology. This paper introduces the system and UWB network architecture based on ECMA-368 standard, moreover it provides a novel analytical tool to evaluate the energy consumption and delay during network set-up.

In this paper, a cross-layer design approach has been used to evaluate the effect of forward error correction (FEC) on energy consumption of non-coherent energy detector receiver using impulse radio ultra-wideband in the context of wireless sensor networks. The proposed method captures relevant characteristics of the physical and medium access control (MAC) layers, while taking into account bit error probability (BEP) requirement of the application. A two-stage semi-analytical optimization model and code rate selection algorithm has been developed to find out the optimal code rate from the energy efficiency perspective. Firstly, a signal-to-noise ratio (SNR) gap analysis is used to select the code rates, which can provide the same target BEP as uncoded transmission, with lower received SNR. Secondly, an energy consumption model is used to explore which one of the selected code rates provide the highest energy saving, when compared to the uncoded case. In this work, the proposed algorithm has been executed for Reed-Solomon codes using Nakagami-m fading channel model and taking into account the channel access success probability of the Slotted Aloha MAC for different offered traffic loads. The results clearly illustrate the potential energy savings that can be achieved by using FEC and selecting the optimum code rate. The developed model is useful in the selection of code rate for particular communication distances and offered traffic load values.

This paper presents a physical and MAC layer analysis of the recently introduced IEEE 802.15.3c standard for multi Gbps communication at 60 GHz. We find the optimal beamwidth of the transmitting antenna, achieving a trade-off between the Piconet Coordinator discovery and the duration of the contention access period (CAP) of the IEEE 802.15.3c MAC superframe. To find the optimal beamwidth, we first analyze the link budget of 60 GHz based directional communication, to identify the transmitting and receiving antenna gain, and hence the minimum beamwidth required to achieve a specific bit error probability (BEP) for a given distance between transmitter and receiver. We introduce a more efficient method for analytically modeling the binary exponential backoff (BEB) process during the CSMA/CA based CAP of the superframe, using a 1-dimentional Markov chain. Numerical results for the required antenna gain and optimal beamwidth, demonstrate the usefulness of our analysis technique.

Ultra-wide band (UWB) is a promising physical layer technology which potentially enables low power and high rate devices with applications for wireless personal area networks (WPANs) and for wireless body area networks (WBANs). The UWB technology considered in this paper, called multiband UWB, is based on orthogonal frequency division multiplexing (OFDM). Any physical layer technology requires a medium access control (MAC) protocol to be coupled with. This paper focuses on a distributed time division multiple access (TDMA) MAC protocol to support high data rate applications, developed within the WiMedia Alliance (2005). The aim of this paper is to study the dynamic beacon period extension and contraction when a newcomer device joins a existing beacon group (BG) and to evaluate the related energy consumption

Abstract This paper investigates the use of bi‐orthogonal modulations in multiuser communication systems based on ultra wide band impulse radio (UWB‐IR) technology: the communication systems considered herein use Gaussian waveforms in AWGN channel and rely on the utilization of a time‐hopping spreading technique. A hybrid pulse modulation is defined, which is obtained by combining pulse amplitude modulation (PAM) and pulse position modulation (PPM) techniques. Particularly, we have compared the bi‐orthogonal system performance to the classical orthogonal one, also in the condition of lack of a general synchronism, possibly caused by the presence of interfering users that belong to a separate network. Moreover, we have taken into account the use of an M‐ary alphabet, in the case of orthogonal and bi‐orthogonal modulation schemes. Copyright © 2005 John Wiley & Sons, Ltd.