Small data transmission (SDT) is a novel technique that allows IoT devices to transmit their payload data without a pre-allocated radio resource. However, unresolvable SDT collisions occur due to the unpredictability of IoT traffic. In this paper, we propose a semi-contention-free transmission scheme that combines dedicated time-slot allocation through hashing and random access with access control through a dueling deep Q-network. Focusing on uplink IoT traffic for SDT in a NOMA-enabled network with two clusters of devices, we implement the proposed scheme and demonstrate its effectiveness and performance with respect to throughput, latency, and energy consumption through extensive simulations.

Along the evolution of mobile communication systems during the past decades from 1st generation (1G) to 5th generation (5G), radio access networks (RANs) have been traditionally implemented and deployed based on vendor-specific hardware and proprietary software. In recent years, there is a surge of interests and efforts among mobile network operators (MNOs) in developing RAN solutions based on open interfaces to facilitate flexible operations and versatile functionalities of RANs using reconfigurable hardware and inter-operable software. In the meantime, various industrial and academic stakeholders are keen on developing open-source driven RAN solutions based on commercial-off-the-shelf (COTS) hardware like software defined radio (SDR). In this article, we convey a comprehensive and systematic study on Open RAN technologies spanning from the theories (from RAN evolution to Open RAN architecture) and the concepts (from disaggregation and functional split to Open RAN architectures), to commercial and prototype deployments as well as implementation platforms. In addition to an in-depth comparison between the 3rd generation partnership project (3GPP) and Open RAN Alliance (O-RAN) interfaces and functions, we shed light on the spectrum allocation aspects for Open RAN deployment covering both public and private 5G networks. Furthermore, this article presents two prototype 5G networks that we have developed based on COTS hardware and open-source software suites as well as the configuration and performance of these prototype proof-of-concept on-campus networks.

The unprecedented surge of massive Internet of things (mIoT) traffic in beyond fifth generation (B5G) communication systems calls for transformative approaches for multiple access and data transmission. While classical model-based tools have been proven to be powerful and precise, an imminent trend for resource management in B5G networks is promoting solutions towards data-driven design. Considering an IoT network with devices spread in clusters covered by a base station, we present in this paper a novel model-free multiple access and data transmission framework empowered by reinforcement learning, designed for power-domain non-orthogonal multiple access networks to facilitate uplink traffic of small data packets. The framework supports two access modes referred to as contention-based and semi-contention-free, with its core component being a policy gradient algorithm executed at the base station. The base station performs access control and optimal radio resource allocation by periodically broadcasting two control parameters to each cluster of devices that considerably reduce data detection failures with a minimum computation requirement on devices. Numerical results, in terms of system and cluster throughput, throughput fairness, access delay, and energy consumption, demonstrate the efficiency and scalability of the framework as network size and traffic load vary.

The burgeoning growth of massive machine-type communication or massive Internet of things traffic in beyond fifth-generation communication systems calls for novel solutions for medium access. In this paper, we propose a reinforcement learning (RL)-based random access scheme for non-orthogonal multiple access (NOMA)-enabled uplink transmissions and investigate how RL can potentially bring benefits for medium access under various network configurations and traffic load conditions. Aiming to mitigate network congestion and enhance overall network performance, we introduce access control and compare network performance of the RL-based access scheme with two benchmark schemes. For performance assessment, we define system and cluster throughput as the key performance metrics. This study provides valuable insights on the feasibility and efficacy of RL-based access control mechanisms across low and high device density scenarios.

To enable concurrent transmissions for Internet of Things (IoT) traffic in multiantenna beyond fifth generation networks, nonorthogonal multiple access (NOMA) mechanisms appear as a promising approach. For NOMA-enabled transmissions, IoT devices are grouped into clusters in order to exploit the benefit of concurrent transmissions. However, how to facilitate transmissions from both intra- and intercluster is not an easy task and the performance of such concurrent transmissions is so far not well understood from a mathematical point of view, especially when error-prone channel conditions are considered. In this article, we propose two random access schemes which enable intra- and intercluster concurrent transmissions for uplink IoT traffic with and without access control. To assess the performance of such systems, we develop two analytical models based on discrete-time Markov chains (DTMCs) that mimic the behavior of such transmissions. Our models deal with cluster-level performance considering dynamic packet arrivals and the transmissions from devices belonging to the same or different clusters. Through extensive simulations, we validate the accuracy of the analytical models and evaluate the system- and cluster-level performance in terms of throughput and delay under various traffic load conditions and network configurations.

To obtain benefits for non-orthogonal multiple access (NOMA) based concurrent transmissions for uplink Internet of things (IoT) traffic in multi-antenna enabled networks, device clustering has been a challenging task. Most previous studies focused on grouping devices into clusters that are served by different beams in multiple input multiple output (MIMO)-NOMA networks. In this paper, we perform an exploratory study on the impact of both intra- and inter-cluster interference on the performance of uplink concurrent transmissions considering that multiple clusters are served by a single beam. For performance assessment, we define two metrics, cluster throughput and transmission latency, and evaluate network performance with various network configurations. The study provides insight on how to configure device clusters and perform access control in order to maximize performance and improve fairness. As devices closer to the base station experience less path attenuation, we introduce distinct access control mechanisms to improve transmissions fairness for concurrent transmissions from difference clusters.

To address the challenges faced by non-orthogonal multiple access (NOMA) for multiple access in beyond fifth gen-eration (B5G) networks, rate-splitting multiple access (RSMA) has newly emerged as a promising approach. In addition to achieving high data rates, RSMA may be used for massive machine-type communication (mMTC)/massive Internet of things (mIoT) applications as well. Although RSMA addresses the user coupling and scheduling overhead problems met by NOMA, it is not clear whether and how RSMA can be applied to uplink mMTC/mIoT traffic. In this study, we explore the applicability of RSMA for uplink traffic and investigate whether there is any benefit to employ RSMA and if yes how this benefit can be achieved. To this end, we propose a novel uplink RSMA scheme with two constituent components, known as inter-device decoding and intra -device decoding, respectively. Through user pairing for inter-device decoding and power allocation for intra-device decoding, we reveal under which circumstances RSMA can bring benefits for uplink traffic.

Although the number of massive machine type communications (mMTC) devices covered by a fifth generation (5G) cell could be huge, not all devices are always active. For radio resource allocation, it is vital that a base station has the knowledge on the number of active mMTC devices in each frame. In this paper, we develop a mathematical framework to perform pseudo-Bayesian estimation on the number of active devices within a 5G new radio (NR) subframe. The estimation is performed by the base station on a subframe-by-subframe basis based upon which a transmission permission probability is imposed on active devices for their transmissions in the next subframe. The active devices include both backlogged devices and new arrivals in the current subframe that will attempt for medium access in the next subframe relying on a combination of NR radio resources in both time and frequency domains. Such an estimation constitutes an important component for the design of grant-free access schemes for mMTC uplink traffic.

In wake-up radio (WuR) enabled Internet of things (IoT) networks, a data communication occurs in a synchronous or asynchronous manner initiated either by a transmitter or receiver. A synchronous transmission is triggered when multiple devices report an event simultaneously, or by a common wake-up call. In this paper, we focus on synchronous transmissions and propose a multicast triggered${s}$ynchronous${t}$ransmission protocol, abbreviated as MURIST, which enables contention based and coordinated data transmissions among distributed devices in order to reduce transmissions latency and energy consumption. Furthermore, we develop a novel analytical model based on an absorbing Markov chain to evaluate the performance of MURIST in a network cluster. Unlike existing models that are merely targeted at the behavior of a single device, the novelty of our model resides in a generic framework to assess the behavior of a cluster of devices for synchronous data transmissions. Based on the analytical model, we obtain closed-form expressions for the distributions of successful and discarded transmissions, number of collisions, and delay, as well as for energy consumption. Extensive simulations are performed to validate the accuracy of the analytical model and evaluate the performance of our scheme versus that of two other schemes.

Although indoor positioning has long been investigated by various means, its accuracy remains concern. Several recent studies have applied machine learning algorithms to explore wireless fidelity (WiFi)-based positioning. In this paper, we propose a novel deep learning model which concatenates an auto-encoder with a long short term memory (LSTM) network for the purpose of WiFi fingerprint positioning. We first employ an auto-encoder to extract representative latent codes of fingerprints. Such an extraction is proven to be more reliable than simply using a deep neural network to extract representative features since a latent code can be reverted back to its original input. Then, a sequence of latent codes are injected into an LSTM network to identify location. To assess the accuracy and effectiveness of our model, we perform extensive real-life experiments.

Although grant-based mechanisms have been a predominant approach for wireless access for years, the additional latency required for initial handshake message exchange and the extra control overhead for packet transmissions have stimulated the emergence of grant-free (GF) transmission. GF access provides a promising mechanism for carrying low and moderate traffic with small data and fits especially well for massive machine type communications (mMTC) applications. Despite a surge of interest in GF access, how to handle heterogeneous mMTC traffic based on GF mechanisms has not been investigated in depth. In this paper, we propose a priority enabled GF access scheme which performs dynamic slot allocation in each 5G new radio subframe to devices with different priority levels on a subframe-by-subframe basis. While high priority traffic has access privilege for slot occupancy, the remaining slots in the same subframe will be allocated to low priority traffic. To evaluate the performance of the proposed scheme, we develop a two-dimensional Markov chain model which integrates these two types of traffic via a pseudo-aggregated process. Furthermore, the model is validated through simulations and the performance of the scheme is evaluated both analytically and by simulations and compared with two other GF access schemes.

The evolution of Internet of things (IoT) towards massive IoT in recent years has stimulated a surge of traffic volume among which a huge amount of traffic is generated in the form of massive machine type communications. Consequently, existing network infrastructure is facing challenges when handling rapidly growing traffic load, especially under bursty traffic conditions which may more often lead to congestion. By proactively predicting the occurrence of congestion, we can implement necessary means and conceivably avoid congestion. In this paper, we propose a machine learning (ML) based model for predicting successful preamble transmissions at a base station and subsequently forecasting the possible occurrence of congestion under bursty traffic conditions. The model is composed of a recurrent neural network ML algorithm which is built based on the long short-term memory architecture. Through extensive simulations, we demonstrate that the proposed model achieves precise predictions on successful preamble transmissions relying merely on the data collected priori to congestion occurrence.

To achieve ultra-low energy consumption and decade-long battery lifetime for Internet of things (IoT) networks, wake-up radio (WuR) appears as an eminent solution. While keeping devices in deep sleep for most of the time, a WuR enabled IoT device can be woken up for data transmission at any time by a wake-up call (WuC). However, collisions happen among WuCs for transmitter-initiated data reporting and among data packets for receiver-initiated data collection. In this paper, we propose two novel hashing-based schemes in order to achieve collision-free data transmissions for receiver-initiated data collection. We consider first a simple scenario in which all devices in a region of interest are covered by a data collector and propose a scheme which facilitates a scheduled time for data uploading of each device. Then we extend our scheme to cover a more realistic scenario where IoT devices are distributed across a larger region that cannot be covered by a single data collector. In this case, we propose a partitioning algorithm for data collection across multiple partitions. Both analysis and simulations are performed to demonstrate the effectiveness of the proposed schemes.

The diversity of application scenarios in 5G mobile communication networks calls for innovative initial access schemes beyond traditional grant-based approaches. As a novel concept for facilitating small packet transmission and achieving ultra-low latency, grant-free communication is attracting lots of interests in the research community and standardization bodies. However, when a network consists of both grant based and grant-free based end devices, how to allocate slot resources properly between these two categories of devices remains as an unanswered question. In this paper, we propose a Markov decision process based scheme which dynamically allocates grant-free resources based on a specific reliability or priority requirement. The performance of the proposed scheme is evaluated via both analysis and simulations under various traffic arrival conditions.

At a density of one million devices per square kilometer, the10’s of billions of devices, objects, and machines that form a massive Internet of things (mIoT) require ubiquitous connectivity. Among a massive number of IoT devices, a portion of them require ultra-reliable low latency communication (URLLC) provided via fifth generation (5G) networks, bringing many new challenges due to the stringent service requirements. Albeit a surge of research efforts on URLLC and mIoT, access mechanisms which include both URLLC and massive machine type communications (mMTC) have not yet been investigated in-depth. In this paper, we propose three novel schemes to facilitate priority-based initial access for mIoT/mMTC devices that require URLLC services while also considering the requirements of other mIoT/mMTC devices. Based on a long term evolution-advanced (LTE-A) or 5G new radio frame structure, the proposed schemes enable device grouping based on device vicinity or/and their URLLC requirements and allocate dedicated preambles for grouped devices supported by flexible slot allocation for random access. These schemes are able not only to increase the reliability and minimize the delay of URLLC devices but also to improve the performance of all involved mIoT devices. Furthermore, we evaluate the performance of the proposed schemes through mathematical analysis as well as simulations and compare the results with the performance of both the legacy LTE-A based initial access scheme and a grant-free transmission scheme.

Massive machine-type communication (mMTC) is expected to play a pivotal role in emerging 5G networks. Considering the dense deployment of small cells and the existence of heterogeneous cells, an MTC device can discover multiple cells for association. Under traditional cell association mechanisms, MTC devices are typically associated with an eNodeB with highest signal strength. However, the selected eNodeB may not be able to handle mMTC requests due to network congestion and overload. Therefore, reliable cell association would provide a smarter solution to facilitate mMTC connections. To enable such a solution, a hidden Markov model (HMM) based machine learning (ML) technique is proposed in this paper to perform optimal cell association. As such, we consider MTC devices with network-assisted decision-making capabilities for selecting the most appropriate eNodeB for data transmission. The proposed HMM based ML technique focuses mainly on the reliability and availability of network resources. Correspondingly, two schemes are developed based on the classical reliability function and the next probable state of the HMM. Based on simulations under various configurations, we demonstrate the advantage of the proposed schemes over a random cell selection scheme.

Ultra-reliable low latency communication (URLLC) and massive machine type communications (mMTC) are two of the three major technological pillars in 5G. For medium access in mMTC scenarios, e.g., smart cities, a major bottleneck for achieving reliable access is channel congestion due to LTE-A based random access. Hence, priority-based access schemes are preferred in order to provide reliable and low latency access for mMTC devices in 5G networks. In this paper, we categorize the devices covered inside a cell into grouped and non-grouped sets and propose a preamble reservation based 2-step access scheme where grouped devices gain network access via a designated group leader using reserved preambles. Through analysis and simulations, we demonstrate that the proposed scheme enables ultra-reliable and low latency access for grouped devices while improving the performance of non-grouped devices through proper configuration of parameters.

Wireless sensor networks (WSNs) are one of the key enabling technologies for the Internet of things (IoT). In such networks, wake-up radio (WuR) is gaining its popularity thanks to its on-demand transmission feature and overwhelming energy consumption superiority. Despite this advantage, overhearing still occurs when a wake-up receiver decodes the address of a wake-up call (WuC) which is not intended to it, causing a certain amount of extra energy waste in the network. Moreover, long latency may occur due to WuC address decoding since WuCs are transmitted at a very low data rate. In this paper, we propose two schemes, i.e., early sleeping (ES) and early data transmission (EDT), to further reduce energy consumption and latency in WuR-enabled IoT/WSNs. The ES scheme decodes and validates an address bit-by-bit, allowing those non-destined devices go to sleep at an earlier stage. The EDT scheme enables a sender to transmit small IoT data together with WuC packets so that the main radio does not have to be in full operation for data reception. We implement both schemes through a WuR testbed. Furthermore, we present a framework based on M/G/1 and assess the performance of the schemes through both theoretical analysis and simulations.

Ultra-reliable low latency communication (URLLC), which refers to achieving almost 100% reliability at a certain (satisfactory) level of services and stringent latency, is one of the key requirements for 5G networks. However, most prior studies on reliable communication did not address space domain analysis. Neither were they pursued from a dependability perspective. This paper addresses the ultra-reliable communication (URC) aspect of URLLC and aims at advocating the concept of URC from a dependability perspective in the space domain. We perform in-depth analysis on URC considering both the spatial characteristics of cell deployment and user distributions, as well as service requirements. We first introduce the concepts of cell availability and system availability in the space domain, then perform connectivity-based availability analysis by considering a Voronoi tessellation where base stations (BSs) are deployed according to a certain distribution. Moreover, we investigate the relationship between signal-to-interference-plus-noise ratio (SINR), user requirement, and achievable cell or system availability by employing both Poisson point process (PPP) and determinantal point process (DPP) BS distributions. For SINR-based availability analysis, coverage contours are identified. Considering further the user distribution in a region of interest, expressions for system availability are derived from users' perspective. Furthermore, we propose an algorithm which could be used for availability improvement based on the calculated availability level. Numerical results obtained considering diverse network scenarios and cell deployments with multiple cells and multiple topologies illustrate the achievable availability under various circumstances.

Wake-up Radios (WuRs) are becoming more popular in Internet of Things (IoT) networks owing to their overwhelming advantages such as low latency, high energy saving, and on-demand communication. In a multi-hop WuR-IoT network, route establishment between source and destination prior to actual data communications consumes a significant portion of energy. To reduce energy consumption and protocol overhead for route establishment, we propose a lightweight relay (LR) selection scheme, referred to as LR-WuR, where a lookup table and acknowledgment are used for next hop relay selection. We develop an analytical model to evaluate the performance of LR-WuR. Extensive simulations are performed to validate the accuracy of the analytical model. Furthermore, we present a framework for deriving optimal network parameters.

Reliable communication is a fundamental service level agreement criterion in wireless networks. Moreover, it is a performance indicator for ultra- reliable communication (URC) in emerging 5G networks. In URC, the quality of the delivered services to end-users ultimately depends on the availability of network resources as well as the quality of the received signal. Therefore, in order to analyze URC in cellular networks, both time- dependent spectrum availability and space-dependent service quality need to be considered. In this paper, we present a combined time and space domain analysis on network reliability based on a continuous time Markov chain model. To this end, we introduce a new reliability metric that indicates the reliability level of URC for downlink transmissions. The metric computes the probability that a user located at a distance d from its base station can access a channel at time t with a received power level greater than a pre-defined threshold value, PTH. Moreover, the impact of channel failures on network performance is also analyzed.

Wake-up Radio (WuR)-enabled wireless personal area networks (WPANs) are more popular over conventional WPANs thanks to WuR's on-demand transmission feature and overwhelming energy consumption superiority. In a WuRenabled WPAN, overhearing occurs when a wake-up receiver decodes and validates the address of a wake-up call which is not intended to it. However, such overhearing consumes a portion of the required reception energy for unintended nodes. To diminish overhearing thus conserve total reception energy in a network, we propose a bit-by-bit address decoding (BBAD) scheme and compare it with another addressing scheme for WuR that uses a micro-controller unit to decode and match the whole sequence of an address. Instead of decoding and validating a complete address at a time, BBAD decodes and matches an address in a bit- by-bit manner. We implement both address decoding schemes through a WuR testbed. Furthermore, we develop a framework based on M/G/1 and assess the performance of the WuR-enabled WPANs through both analysis and simulations.

In wake-up radio (WuR) enabled wireless sensor networks (WSNs), the envisaged application scenarios are primarily targeted at low traffic load conditions. When applying WuR to medium or heavy traffic load scenarios, however, collisions among wake-up calls (WuCs) may happen, resulting in a lower packet delivery ratio (PDR). In this paper, we propose a media access control protocol for WuR- enabled WSN that is capable of avoiding WuC collisions by activating a contention-based collision avoidance mechanism for WuC transmissions. The performance of the proposed protocol is evaluated by a Markov chain based mathematical model and is compared with a WuR protocol that performs only clear channel assessment for WuC transmissions. Numerical results demonstrate that our proposed protocol achieves better performance in terms of both PDR and network throughput.

Emerging 5G mobile networks envisage ultra-reliable communication (URC) as one of the major requirements for anytime anywhere communication. Although URC has recently attracted a lot of attention in the research community, existing work seems to rely on approaching reliability merely from a time domain perspective. However, both time and space domain parameters affect reliability and need to be investigated. This paper introduces a dependability theory based definition for per-user availability targeted at 5G networks. The advocated definition promotes both space and time domain components for URC provisioning. Furthermore, we perform reliability and availability analysis and simulations considering various network scenarios and mobility patterns.

Energy harvesting (EH) delivers a unique technique for replenishing batteries in Internet of Things (IoT) devices. Equipped with an EH accessory, EH-enabled sensor nodes/IoT devices extract energy from ambient resources, such as solar or radio frequency (RF) signals. Relying on residual battery or/and harvested energy, sensor nodes in an IoT network perform data exchange activities. Otherwise, the delivery of sensed data would be delayed until sufficient energy is harvested. In this paper, we propose an on-demand energy requesting (OER) mechanism for improving the delay performance of a wireless EH-powered IoT network. The proposed scheme acquires energy when necessary from an energy transmitter that is capable of transmitting energy via directed RF signals. Furthermore, we develop two associated discrete time Markov chain (DTMC) models to analyze the performance of the OER scheme, targeting at a generic synchronous medium access control (MAC) protocol. Using the proposed DTMC models, we evaluate OER with respect to average packet delay, network throughput, packet loss probability, and packet reliability ratio by employing a specific synchronous MAC protocol. Numerical results obtained from both analysis and discrete-event simulations coincide with each other, indicating the accuracy of the models and revealing the behavior of EH-based packet transmissions.

In wake-up radio (WuR) enabled wireless sensor networks (WSNs), a node triggers a data communication at any time instant by sending a wake-up call (WuC) in an on-demand manner. Such wake-up operations eliminate idle listening and overhearing burden for energy consumption in duty-cycled WSNs. Although WuR exhibits its superiority for light traffic, it is inefficient to handle high traffic load in a network. This paper makes an effort towards improving the performance of WuR under diverse load conditions with a twofold contribution. We first propose three protocols that support variable traffic loads by enabling respectively clear channel assessment (CCA), backoff plus CCA, and adaptive WuC transmissions. These protocols provide various options for achieving reliable data transmission, low latency, and energy efficiency for ultralow power consumption applications. Then, we develop an analytical framework based on an M/G/1/2 queue to evaluate the performance of these WuR protocols. Discrete-event simulations validate the accuracy of the analytical models.

Providing channel access opportunities for new service requests and guaranteeing continuous connections for ongoing flows until service completion are two challenges for service provisioning in wireless networks. Channel failures, which are typically caused by hardware and software failures or/and by intrinsic instability in radio transmissions, can easily result in network performance degradation. In cognitive radio networks (CRNs), secondary transmissions are inherently vulnerable to connection breaks due to licensed users' arrivals as well as channel failures. To explore the advantages of channel reservation on performance improvement in error-prone channels, we propose and analyze a dynamic channel reservation (DCR) algorithm and a dynamic spectrum access (DSA) scheme with three access privilege variations. The key idea of the DCR algorithm is to reserve a dynamically adjustable number of channels for the interrupted services to maintain service retainability for ongoing users or to enhance channel availability for new users. Furthermore, the DCR algorithm is embedded in the DSA scheme enabling spectrum access of primary and secondary users with different access privileges based on access flexibility for licensed shared access. The performance of such a CRN in the presence of homogeneous and heterogeneous channel failures is investigated considering different channel failure and repair rates.

Energy harvesting (EH) promises an extended lifetime for wireless sensor networks (WSNs), supplying sensor nodes with accumulated energy from natural sources. Different from battery powered sensors, nodes in EH-enabled WSNs are equipped with an energy harvesting accessory in order to extract energy from surrounding sources. Based upon the harvested energy, sensor nodes perform data exchange activities. In this paper, we develop two discrete time Markov chain (DTMC) models to analyze the performance of packet transmissions in such a WSN while employing a generic synchronous medium access control (MAC) protocol. Using the proposed DTMC models, we investigate the effect of EH over a specific synchronous MAC protocol with respect to average packet delay and network throughput. Furthermore, the analytical results are validated via discrete-event simulations. Numerical results indicate the accuracy of the models and reveal the behavior of packet transmissions relying on harvested energy.

To address the challenge of ever-growing data rate demand and benefit from the popularity of WiFi capability in mobile phones, 3GPP is studying techniques which enable the coexistence of WiFi and LTE in the unlicensed band, known as LTEU. Two flavors of the listen before talk (LBT) principle, referred to as load based equipment (LBE) and frame based equipment (FBE), are recommended by 3GPP. In this paper, we investigate two enhanced FBE mechanisms, i.e., 1) enhanced FBE (E-FBE); and 2) backoff and idle time reduction FBE (BITR-FBE) for the purpose of improving FBE. After presenting the idea of E-FBE, we propose BITR-FBE which can further improve throughput, shorten delay and reduce energy consumption of LTE-U or WiFi devices. The performance of these both mechanisms is evaluated through Markov modeling and simulations with respect to throughput, delay, energy consumption as well as transmission opportunities under both homogeneous and heterogeneous network scenarios.

Cooperative transmission (CT) enables balanced energy consumption among sensor nodes and mitigates the energy hole problem in wireless sensor networks (WSNs). In typical CT enabled medium access control (MAC) protocols, a source node decides to trigger CT or not based on a residual energy comparison between itself and its relay node. In this paper, we propose a receiver initiated CT MAC protocol, in which the receiving node makes the decision on initiating CT or not based on a tradeoff between performing CT and non-CT. In this way, nodes can avoid idle listening and achieve an extended lifetime. A discrete-time Markov chain (DTMC) model is developed to analyze the performance of CT associated with synchronous CT MAC protocols. Using this DTMC model, the performance of the protocol is evaluated with respect to energy consumption, energy efficiency and network lifetime. Numerical results demonstrate the accuracy of the model and the effectiveness of CT, in contrast to non-CT, as it leads to balanced energy consumption and an optimal network lifetime.

To address the burgeoning demand for mobile data, 3GPP is actively studying the capability of operating LTE in the unlicensed band, referred to as LTE-U. One of the main challenges of this approach is to maintain better coexistence between WiFi and LTE-U devices. To enable the coexistence, the listen before talk (LBT) principle has been adopted for LTE-U medium access with two flavors of mechanisms, i.e., load based equipment (LBE) and frame based equipment (FBE) access. In this paper, we consider the FBE mechanism and enhance its performance by introducing a backoff procedure for LTE devices. We investigate the original FBE mechanism defined by 3GPP and the enhanced FBE (E- FBE) mechanism from our earlier work. Then we propose a novel FBE mechanism by both enabling a backoff approach for access contention and eliminating the unnecessary waiting time for nodes which failed in previous transmission contention. Furthermore, we compare the performance of these three mechanisms with respect to four parameters. Numerical results based on simulations demonstrate that the proposed mechanism outperforms the other two in terms offairnessindex,transmissionopportunities,collisio nprobability, as well as transmission delay.

Many recent studies anticipate that wake-up radio (WuR) will replace traditional duty-cycled (DC) protocols given its overwhelming performance superiority on energy consumption. Meanwhile, the question on whether WuR performs always better than DC protocols has not been answered explicitly. In this paper, we investigate in-depth the energy consumption performance of WuR by considering various levels of traffic load in a wireless sensor network. By comparing SCM-WuR with both synchronous MAC (S-MAC) and asynchronous MAC (X-MAC), we ascertain that SCM-WuR does consume orders of magnitude lowerenergythanDCprotocolswhentrafficloadislow.Howe ver, our numerical results reveal at the same time that SCM-WuR does not have an absolute advantage when traffic load is heavy or saturated, especially when long range wake-up call is targeted.

Overhearing and idle listening are two primary sources for unnecessary energy consumption in wireless sensor networks. Although introducing duty cycling in medium access control (MAC) reduces idle listening, it cannot avoid overhearing in a network with multiple contending nodes. In this paper, we propose an event-triggered sleeping (ETS) mechanism for synchronous duty-cycled (DC) MAC protocols in order to avoid overhearing when a node is not active. This ETS mechanism applies to any synchronous DC MAC protocols and makes them more energy efficient. Furthermore, we develop a two dimensional discrete time Markov chain model to evaluate the performance of the proposed ETS mechanism by integrating it to a popular synchronous DC MAC protocol namely sensor-MAC. Using the developed model, energy consumption, energy efficiency and network lifetime are calculated. Numerical results obtained through both analytical model and discrete-event simulations demonstrate the effectiveness of the ETS mechanism, represented by lower energy consumption, higher energy efficiency and longer lifetime when compared with the conventional control packet triggered sleeping mechanism.

It is well understood that in wireless networks, channel failures, which are typically caused by equipment or power failures as well as intrinsic features in radio transmissions, such as fading and shadowing, can easily result in network performance degradation. Therefore, fast recovery from channel failures is an important measure that should be incorporated with those networks. Consequently, in a cognitive radio network (CRN), channel failures can cause significant performance degradation in both primary and secondary networks. Instead, retainability, i.e., the capability of providing continuous connection for users must be guaranteed even if a significant network element is disrupted. In this paper, we develop an analytical model to analyze the system performance of CRNs with a focus on random channel failures. In addition to performance analysis under channel failures, a channel reservation scheme is proposed. The scheme can be adopted in dynamic channel access strategies in order to prioritize ongoing sessions over new user requests. Furthermore, optimal channel reservations subject to different performance requirements are also studied.

To ensure quality of service (QoS) for heterogeneous traffic in IEEE 802.15.4 based wireless sensor networks (WSNs) is a challenging task since no traffic prioritization mechanism is defined in such WSNs. In this paper, we propose two priority-oriented multicast transmission schemes to provide QoS for heterogeneous traffic in WSNs. Contrary to the legacy CSMA/CA and FIFO principles, these schemes differentiate self-generated or received traffic and give priority to delay-sensitive traffic with respect to channel access and packet scheduling. Simulations are performed in order to assess the performance of these schemes in terms of end-to-end delay, energy consumption, packet delivery ratio, and collision probability.

Punctual and reliable transmission of collected information is indispensable for many Internet of Things (IoT) applications. Such applications rely on IoT devices operating over wireless communication links which are intrinsically unreliable. Consequently to improve packet delivery success while reducing delivery delay is a challenging task for data transmission in the IoT. In this paper, we propose an improved distributed stochastic routing algorithm to increase packet delivery ratio and decrease delivery delay in IoT with unreliable communication links. We adopt the concept of absorbing Markov chain to model the network and evaluate the expected delivery ratio and expected delivery delay over multiple hops. Simulations are performed in order to evaluate the performance of the proposed algorithm in comparison with three existing decentralized routing algorithms.

To ensure end-to-end reliable multicast or broadcast transmissions in IEEE 802.15.4 based wireless sensor networks WSNs) is a challenging task since no retransmission and acknowledgment mechanisms are defined in such WSNs. In this paper, we propose three retransmission enabled multicast transmission schemes in order to achieve reliable packet transmissions in such networks. Different from the legacy CSMA/CA principle, these schemes allow a sending or forwarding node to retransmit a packet if necessary and enable implicit or/and explicit acknowledgment for multicast services. Simulations are performed in order to assess the performance of these schemes in terms of number of retransmissions, packet loss, energy consumption, collision probability and end-to-end delay.

Due to limited energy capacity in mobile devices, energy harvesting is regarded as a promising technology for lifetime extension in device-to-device (D2D) communication. However, medium access control (MAC) protocols designed for D2D communication intrinsically do not consider the existence of harvested energy. In this paper we study four backoff (BO) algorithms, among which one algorithm is proposed to enhance the BO selection based on energy harvesting rate and residual energy of devices. Simulations are performed in order to assess how the proposed algorithm can extend the lifetime of a D2D communication network as well as to provide fair channel access opportunities among devices.

Channel aggregation (CA) techniques can offer flexible channel allocation and improve overall system performance in multi-channel cognitive radio networks (CRNs). Although many CA techniques have been proposed and studied, the impact of guard-band on CA for channel access has not been addressed in-depth. In this paper, we study the guard-band allocation mechanisms in discontinuous-orthogonal frequency division multiplexing (D-OFDM) based CRNs, and investigate the impact of guard-band sharing on SU flows when CA is enabled. Continuous time Markov chain (CTMC) based models have been developed in order to investigate the stochastic behavior of PU and SU flows. Based on our mathematical analysis and simulation results, we observe that when guard-band is considered together with CA, the performance of the network varies according to different access schemes with distinct guard-band allocation mechanisms.

Synchronized duty cycling (DC) aligns sensor nodes to wake up at the same time in order to reduce idle listening for medium access control (MAC) in wireless sensor networks (WSNs). Demand wakeup MAC (DW-MAC) is a popular synchronous DC MAC protocol which allows nodes to compete and transmit multiple packets in one operational cycle. This multiple packet transmission (MPT) feature makes DW-MAC more energy efficient when comparing with other existing single time competition based protocols such as sensor MAC (S-MAC). In the literature, no analytical model exists to evaluate the performance of DW-MAC. In this paper, we develop two associated discrete time Markov chain (DTMC) models and incorporate them with each other for performance evaluation of DW-MAC with MPT. Using the proposed models, energy consumption and network lifetime are calculated. Furthermore, the proposed models are validated through discrete-event simulations.

Wireless sensor networks (WSNs) consist of connected low-cost and small-size sensor nodes. The sensor nodes are characterized by various limitations, such as energy availability, processing power, and storage capacity. Typically, nodes collect data from an environment and transmit the raw or processed data to a sink. However, the collected data contains often redundant information. An in-network processing scheme attempts to eliminate or reduce such redundancy in sensed data. In this paper, we propose two in-network data processing schemes for WSNs, which are built based on a lightweight algebra for data processing. The schemes bring also benefits like decreased network traffic load and increased reliability for a network. For trust generation, we employ subjective logic based calculations to mitigate trust fluctuations caused by internal and external factors. Numerical results based on synthetic data reveal the effectiveness and preciseness of our proposed schemes.

Spectrum leasing has been proposed as an effective approach for enabling more flexible spectrum utilization in CRNs. In CRNs, a primary network (PN) which consists of multiple primary users (PUs) can lease part of the licensed spectrum to secondary users (SUs) in exchange for operational benefits. The focus of this study is to investigate how and to what extent the PN allows spectrum leasing in CRNs, considering the QoS requirements of the PN and the secondary network (SN). Correspondingly, we propose two dynamic spectrum leasing strategies, which can improve the QoS performance of SUs while ensuring sufficient remuneration for PUs. In order to dynamically adjust the portion of leased bandwidth, two forms of leasing algorithms, which are based on channel occupancy of the PN and the SN respectively are proposed. Analytical models are developed to characterize system centric performance metrics including capacity, blocking probability, and forced termination probability in both networks. Furthermore, a dynamic pricing scheme for spectrum leasing and utility-based resource allocation is introduced. Finally the performance of dynamic leasing is compared quantitatively with that of static leasing and approaches without leasing. Numerical results obtained from both analysis and simulations show that dynamically adjusted spectrum leasing improves network performance.

Spectrum leasing in cognitive radio networks (CRNs) allows the primary network (PN) to lease a certain fraction of its licensed bandwidth to the secondary network (SN). The motivation for such a concept is to enhance the performance of SNs while improving channel utilization. Meanwhile, the license owners of the channels can also gain benefits through spectrum leasing in terms of either monetary rewards or cooperative communications. In this paper, we propose three dynamic channel access strategies for spectrum leasing in multi-channel CRNs. A common characteristic of all these strategies is that the priority for channel access over the leased spectrum is given to SNs and the unleased spectrum to PNs respectively. The distinction among these three strategies is at the level of opportunistic or exclusive access to leased and unleased spectra by an SN or a PN. The performance of the proposed strategies is evaluated and compared with each other in terms of several system centric metrics including capacity, blocking probability, forced termination probability and channel utilization efficiency.

One of the main challenges confronted by wireless sensor networks (WSNs) is to reduce energy consumption of nodes for the purpose of network lifetime extension. In the literature, many backbone based protocols such as connected dominating set (CDS) and broadcast or multicast based protocols are employed in order to improve network performance in terms of metrics like energy consumption, number of transmissions and dissemination delay. In this paper, we evaluate the performance of a recently proposed transmission protocol known as collective flooding (CF), which is based on link correlation, under various link correlation conditions. Through simulations and analyses we demonstrate that although CF performs well in most cases in comparison with CDS and multicast based protocols, weak link correlation could cause serious performance degradation for CF based data transmissions. Accordingly, we propose two techniques and demonstrate that they improve significantly the performance of CF under weak link correlation.

Consider an underlay cognitive relay network with multiple source and destination pairs and that a decode-and-forward scheme is adopted at the relay. We propose a multi-phase transmission protocol in this paper which involves cooperation among source, relay and destination nodes. Given perfect interference elimination before decoding at the destination nodes, we derive closed-form expressions for outage probability calculation over Rayleigh fading channels. Furthermore, the optimal relay power allocation factor which leads to minimal outage probability is determined. Numerical results reveal the conditions under which satisfactory performance can be achieved based on the proposed scheme.

Welcome to the special issue of IET Communications on device-to-device (D2D) communications. As more and more new mobile multimedia rich services are becoming available to larger audiences, there is an ever increasing demand for higher data rate wireless access. Wireless D2D communication is a promising technology to improve user experience and optimise resource utilisation in cellular networks. These benefits are achieved by enabling two or more mobile devices in the proximity of each other to establish a direct local link bypassing the base station or the access point. Significant progress has been made since the introduction of this technology a few years ago. On the other hand, many research challenges still exist for such a new wireless communication paradigm, for example, how to share resources dynamically (e.g. spectrum and energy) between cellular communication and ad hoc D2D communication to accommodate larger volumes of traffic, how to ensure Quality of Service (QoS) to end users, etc. Other challenges include: discovery of services for D2D communication; radio resource allocation and resource management; self-organisation of direct links; proximity-based offloading, and capacity enhancement as well as performance evaluation. The future D2D networks cannot operate efficiently unless these and other relevant challenges are properly addressed. The purpose of this special issue is to address research advances that enable D2D communication in cellular networks, and to report on the state-of-the-art contributions in this area. We are grateful to the overwhelming interest and support from the community, as we received a large body of excellent contributions. Out of the twenty-eight submissions to this special issue, we have selected nine outstanding papers that we believe represent the state-of-art in the device to device communication area. The papers are organised into three groups: two papers on channel coding and signal processing algorithms, seven papers on resource management and scheduling, and five papers on new services and applications. The first group addresses channel coding and signal processing algorithms for the physical layer. The first of these two papers, written by Xiang et al. presents an overview of the state-of-the-art D2D communication on channel measurements and modeling. The future trends and research directions are also comprehensively discussed. The work in this paper will facilitate system design and optimisation in channel-oriented D2D communication. The second paper, by Zhang et al. presents a sub-block tracking based equalisation technique for orthogonal frequency division multiplexing (OFDM) based D2D communications in high mobility environments. By partitioning an OFDM block into several sub-blocks and rendering that the channel response of each sub-block is time-invariant, one can equalise the partitioned sub-block by a single tap. Both theoretical analysis and simulation results demonstrate that the merits of the proposed scheme in high mobility D2D environments. The second group mainly investigates multiple access control (MAC) and network layer resource allocation and scheduling issues. The first paper in this group, written by Dai et al. studies the spectrum sharing problems in heterogeneous D2D networks where different D2D users coexist with the cellular users. A scheme called spectrum partition based D2D transmission is proposed to improve the spectrum efficiency of the D2D and cellular networks. Simulation results are reported to show evident performance gains of the proposed scheme. The second paper, written by Wang et al. exploits historical social interaction information of mobile users for a D2D link setup and resource allocation. It develops a contact time model to characterise the D2D links such that only those D2D links with sufficiently long contact time may be considered for a D2D link setup and resource allocation. This work demonstrates that sociality-aware allocation, compared to sociality-unaware schemes, can achieve better performance. The third paper, by Zheng et al. studies dynamic resource allocation for D2D communication. The authors propose a service time prediction based dynamic resource allocation mechanism. The simulation results show that the proposed mechanism can significantly improve the system performance. The paper, by Kang et al. focuses on link scheduling in D2D networks. The authors propose distributed link scheduling schemes based on a recently proposed D2D communication technology, FlashLinQ. To deal with the inefficiency of resource reuse in FlashLinQ, two new link scheduling schemes based on binary matrix on-off interference map are designed. The performance enhancement over conventional schemes is demonstrated through simulations. Another paper, by Zhou et al. considers the network-controlled D2D multicast with network coding. It proposes a user-specific bit mapping algorithm to make different information with a different equivalent coding rate before performing network-coded. A corresponding user-specific link adaptation scheme is proposed to adaptively choose an optimal modulation and coding scheme for D2D multicast. Numerical results show that the user-specific link adaptation scheme can improve the capacity performance of network controlled D2D multicast. The sixth paper of this group, by Zhou et al. considers the Spectral Efficiency (SE) and the Energy Efficiency (EE) problems in D2D networks. The target is to maximise each User Equipment's EE in an interference-limited environment subject to its specific QoS and maximum transmission power constraints (i.e., EE). The problem is formulated and solved within the framework of non-cooperative game. The tradeoff between EE and SE is analysed and closed-form expressions are also derived. The seventh paper, written by Chen et al. concentrates on user-centric relay assisted D2D communications. A Vickrey-Clarke-Groves auction based relay allocation mechanism (ARM) is proposed. The work is also extended to a general case and a general ARM. Extensive simulation results show the efficiency and effectiveness of the proposed mechanisms. The third group explores new services and applications of D2D communication. The first paper, written by Chu et al. investigates robust secrecy rate optimisation for multiple input and single output (MISO) secrecy channel with multiple D2D communications. Two robust secrecy rate optimisation problems, one for robust power minimisation and the other for robust secrecy rate maximisation are discussed. Simulation results are provided to validate the performance gains. The second paper, by Li et al. proposes a new model for analysing the multi-hop delay of safety-related message broadcasting in V2V communications, taking into account actual traffic factors. A new scheme is proposed to reduce multi-hop delay by tracking the optimal one-hop transmission range and it was validated by simulations using realistic vehicular traces. The third paper, by Sun et al. reviews the standardisation progress of D2D in 3GPP Release 12. Three scenarios, in-coverage, partial-coverage and out-of-coverage, are defined. For these scenarios, channel models are obtained by an amendment to existing channel models. Centralised, distributed and hybrid synchronisation procedures are introduced. The design aspects of D2D discovery and communication are discussed in detail. Possible future work toward post releases is also briefly outlined. The fourth paper, by Xi et al. proposes an efficient hybrid data collection scheme for the machine nodes in hierarchical smart building networks. These concerned nodes can form clusters via distributed methods. The corresponding resource allocation scheme can be realised easily. This cooperative scheme can reduce the signaling overhead and meanwhile enhance the delay or security performance. The last paper, written by Kwak et al. designs a service-oriented networking platform to offer dynamic networking services in supporting mobile group communications among connected smart devices. The proposed platform adopts a session initiation protocol (SIP) protocol as the service signaling protocol that provides high extensibility and compatibility. Also, the quality of end-to-end service is guaranteed by a virtue smart delivery scheme in the platform. In summary, this special issue offers a comprehensive review of recent advances in the area of wireless D2D communication and networks, exposes and addresses the research challenges in physical, MAC as well as application layers. The special issue will serve as a good reference for the academic community for future research ideas, and in the meantime provide valuable concepts and directions for future standardisation and commercialisation in the industry. Finally, we would like to thank all the authors who have submitted their papers for consideration for publication in this issue. We are grateful to the anonymous reviewers who spent much of their precious time in reviewing all the submissions. Their timely reviews and comments greatly helped us select the best papers for inclusion in this special issue. We would also like to thank the devoted staff of IET Communications for their professional support, and particularly express our gratitude to the Editor-in-Chief, Professor Sherman Shen, for his advice, patience, and encouragement from the beginning until the final stage. Lingyang Song received his PhD from the University of York, UK, in 2007, where he received the K.M. Stott Prize for excellent research. He worked as a research fellow at the University of Oslo, Norway, and Harvard University, until rejoining Philips Research UK in March 2008. In May 2009, he joined the School of Electronics Engineering and Computer Science, Peking University, China, as a full professor. His main research interests include MIMO, cognitive and cooperative communications, physical layer security, and wireless ad hoc/sensor networks. He published extensively and wrote 3 text books. He is the recipient of 2012 IEEE Asia Pacific (AP) Young Researcher Award, and received 7 best paper awards including IEEE WCNC, ICC and Globecom. He is currently on the Editorial Board of IEEE Transactions on Wireless Communications, China Communications, and Journal of Network and Computer Applications. He is a senior member of IEEE, and an IEEE ComSoc distinguished lecturer since 2015. Mérouane Debbah entered the Ecole Normale Supérieure de Cachan (France) in 1996 where he received his M.Sc and Ph.D. degrees respectively. He worked for Motorola Labs (Saclay, France) from 1999–2002 and the Vienna Research Center for Telecommunications (Vienna, Austria) until 2003. From 2003 to 2007, he joined the Mobile Communications department of the Institut Eurecom (Sophia Antipolis, France) as an Assistant Professor. Since 2007, he is a Full Professor at Supelec (Gif-sur-Yvette, France). From 2007 to 2014, he was director of the Alcatel-Lucent Chair on Flexible Radio. Since 2014, he is Vice-President of the Huawei France R&D center and director of the Mathematical and Algorithmic Sciences Lab. His research interests are in information theory, signal processing and wireless communications. He is an Associate Editor in Chief of the journal Random Matrix: Theory and Applications and was an associate and senior area editor for IEEE Transactions on Signal Processing respectively in 2011-2013 and 2013-2014. Mérouane Debbah is a recipient of the ERC grant MORE (Advanced Mathematical Tools for Complex Network Engineering). He is a IEEE Fellow, a WWRF Fellow and a member of the academic senate of Paris-Saclay. He is the recipient of the Mario Boella award in 2005, the 2007 IEEE GLOBECOM best paper award, the Wi-Opt 2009 best paper award, the 2010 Newcom++ best paper award, the WUN CogCom Best Paper 2012 and 2013 Award, the 2014 WCNC best paper award as well as the Valuetools 2007, Valuetools 2008, CrownCom2009, Valuetools 2012 and SAM 2014 best student paper awards. In 2011, he received the IEEE Glavieux Prize Award and in 2012, the Qualcomm Innovation Prize Award. Rong Yu received his Ph.D. degree from Tsinghua University, China, in 2007. After that, he worked in the School of Electronic and Information Engineering of South China University of Technology (SCUT). In 2010, he joined the Institute of Intelligent Information Processing at Guangdong University of Technology (GDUT), where he is now a full professor. His research interest mainly focuses on wireless communications and mobile computing. Dr. Yu is currently serving as the deputy secretary general of the Internet of Things (IoT) Industry Alliance, Guangdong, China, and the deputy head of the IoT Engineering Center, Guangdong, China. Frank Y. Li holds a Ph.D. degree from the Norwegian University of Science and Technology (NTNU). He worked as a Senior Researcher at UniK - University Graduate Center, University of Oslo before joining the Department of Information and Communication Technology, University of Agder (UiA) in August 2007 where he is currently a Professor. Dr. Li's research interests include MAC mechanisms and routing protocols in 4G and beyond mobile systems and wireless networks, mesh and ad hoc networks; wireless sensor network; D2D communication; cooperative communication; cognitive radio networks; green wireless communications; QoS, resource management and traffic engineering in wired and wireless IP-based networks; analysis, simulation and performance evaluation of communication protocols and networks. Jianzhong (Charlie) Zhang: Charlie Zhang is currently senior director and head of Wireless Communications Lab with Samsung Research America at Dallas, where he leads technology development, prototyping and standardisation for Beyond 4G and 5G wireless systems. From Aug 2009 to Aug 2013, he served as the Vice Chairman of the 3GPP RAN1 working group and led development of LTE and LTE-Advanced technologies such as 3D channel modeling, UL-MIMO and CoMP, Carrier Aggregation for TD-LTE, etc. Before joining Samsung, he was with Motorola from 2006 to 2007 working on 3GPP HSPA standards, and with Nokia Research Center from 2001 to 2006 working on IEEE 802.16e (WiMAX) standard and EDGE/CDMA receiver algorithms. He received his Ph.D. degree from University of Wisconsin, Madison.

Channel accessibility by a secondary user (SU) in cognitive radio networks (CRNs) depends on the availability of the spectrum based on primary user and other SU activities. A new SU request may be blocked and an ongoing SU service may also be discarded if no sufficient spectrum is available. So far, little work has been done to analyze the reliability and availability aspects of CRNs from the perspective of the dependability theory. In this paper, we introduce the concept of availability for spectrum access in multi-channel CRNs, which is defined as the fraction of time that a CRN can allocate at least the minimum number of required channels for a new SU request. Through a proposed continuous-time discrete-state Markov model, we analyze the performance of CRN channel access schemes in terms of a few reliability-relevant metrics such as mean channel available time and mean time to first channel unavailability. Furthermore numerical results are also presented in this paper and the correctness of the derived theoretical models are verified through simulations.

Unattended Wireless Sensor Networks (UWSNs) are characterized by long periods of disconnected operation and fixed or irregular intervals between sink visits. The absence of an online trusted third party implies that existing WSN trust management schemes are not applicable to UWSNs. In this paper, we propose a trust management scheme for UWSNs to provide efficient and robust trust data storage and trust generation. For trust data storage, we employ a geographic hash table to identify storage nodes and to significantly decrease storage cost. We use subjective logic based consensus techniques to mitigate trust fluctuations caused by environmental factors. We exploit a set of trust similarity functions to detect trust outliers and to sustain trust pollution attacks. We demonstrate, through extensive analyses and simulations, that the proposed scheme is efficient, robust and scalable.

With the implementation of channel assembling (CA) techniques, higher data rate can be achieved for secondary users in multi-channel cognitive radio networks. Recent studies which are based on loss systems show that maximal capacity can be achieved using dynamic CA strategies. However the channel allocation schemes suffer from high blocking and forced termination when primary users become active. In this paper, we propose to introduce queues for secondary users so that those flows that would otherwise be blocked or forcibly terminated could be buffered and possibly served later. More specifically, in a multi-channel network with heterogeneous traffic, two queues are separately allocated to real-time and elastic users and channel access opportunities are distributed between these two queues in a way that real-time services receive higher priority. Two queuing schemes are introduced based on the delay tolerance of interrupted elastic services. Furthermore, continuous time Markov chain models are developed to evaluate the performance of the proposed CA strategy with queues, and the correctness as well as the preciseness of the derived theoretical models are verified through extensive simulations. Numerical results demonstrate that the integration of queues can further increase the capacity of the secondary network and spectrum utilization while decreasing blocking probability and forced termination probability.

Flexible channel allocation may be applied to multi-channel cognitive radio networks (CRNs) through either channel assembling (CA) or channel fragmentation (CF). While CA allows one secondary user (SU) occupy multiple channels when primary users (PUs) are absent, CF provides finer granularity for channel occupancy by allocating a portion of one channel to an SU flow. In this paper, we investigate the impact of CF together with CA for SU flows by proposing a channel access strategy which activates both CF and CA and correspondingly evaluating its performance. In addition, we also consider a novel scenario where CA is enabled for PU flows. The performance evaluation is conducted based on continuous time Markov chain (CTMC) modeling and simulations. Through mathematical analyses and simulation results, we demonstrate that higher system capacity can be achieved indeed by jointly employing both CA and CF, in comparison with the CA-only strategies. However, this benefit is obtained only under certain conditions which are pointed out in this paper. Furthermore, the theoretical capacity upper bound for SU flows with both CF and CA enabled is derived when PU activities are relatively static compared with SU flows.

An attractive approach to overcome capacity limitations in a densely deployed WLAN environment is to enable transmission concurrency. In this paper, we propose a co-channel concurrent transmission scheme, referred to as C2SMA/CA, which determines whether to allow multiple concurrent transmissions based on interference estimation using positional information. A distributed multi-link concurrency scheduling algorithm is implemented, and its performance is evaluated through extensive simulations.

In this paper, we propose a novel routing protocol which is integrated with channel assignment for multi-channel multi-hop wireless ad hoc networks. In such a network, each node is equipped with three transceivers. One is always tuned on a control channel which is responsible for control and broadcast messages, and the other two perform as transmitter and receiver respectively for traffic flows on different data channels. The routing protocol works in an on-demand manner, and the proposed routing discovery process selects a path that potentially traverses nodes with lighter traffic load and lower number of carried flows. With a given number of non-overlapping channels, the optimal solution of channel allocation for multiple flows is shown to be in general NP-hard. Therefore, a heuristic algorithm for channel allocation based on the information acquired along a flow path is adopted, in order to mitigate two types of interference, i.e., inter-path interference and intra-path interference. NS2 based simulation experiments are conducted to evaluate the performance of the proposed protocol.

Energy efficiency has gained its significance when service providers' operational costs burden with the rapidly growing data traffic demand in cellular networks. In this paper, we propose an energy efficiency model for Poisson-Voronoi tessellation (PVT) cellular networks considering spatial distributions of traffic load and power consumption. The spatial distributions of traffic load and power consumption are derived for a typical PVT cell, and can be directly extended to the whole PVT cellular network based on the Palm theory. Furthermore, the energy efficiency of PVT cellular networks is evaluated by taking into account traffic load characteristics, wireless channel effects and interference. Both numerical and Monte Carlo simulations are conducted to evaluate the performance of the energy efficiency model in PVT cellular networks. These simulation results demonstrate that there exist maximal limits for energy efficiency in PVT cellular networks for given wireless channel conditions and user intensity in a cell.

Cognitive radio has been introduced to increase spectrum utilization efficiency. To further improve bandwidth utilization of cognitive radio users, channel aggregation (CA) techniques can be adopted for spectrum access. In this paper, we analyze the complexity of three CA strategies, in terms of required amount of handshakes for channel adaptation due to primary and secondary user activities. Continuous time Markov chain models are developed to evaluate the total number of handshakes required per unit time by different CA strategies and the analytical results are validated by simulations. Numerical results reveal that the complexity of CA strategies depends on the capability and the design principle of spectrum adaptation.

Unattended Wireless Sensor Networks (UWSNs) are characterized by long periods of disconnected operation and fixed or irregular intervals between visits by the sink. The absence of an online trusted third party, i.e., an on-site sink, makes existing trust management schemes used in legacy wireless sensor networks not applicable to UWSNs directly. In this paper, we propose a trust management scheme for UWSNs to provide efficient, robust and scalable trust data storage. For trust data storage, we employ geographic hash table to efficiently identify data storage nodes and to significantly reduce storage cost. We demonstrate, through detailed analyses and extensive simulations, that the proposed scheme is efficient, robust, and scalable.

Motivated by the demand for energy efficiency improvement in mobile communication industry, we explore an idea of optimizing energy efficiency for MIMO-OFDM wireless communication systems while maintaining users' quality of service (QoS) requirement. Based on the binary power control scheme,a power allocation criterion for energy efficiency optimization is derived under the total power constraint. From a bit error rate (BER) point of view, a protection constraint is configured to guarantee the system QoS. With the aim of energy efficiency optimization under QoS guarantee in MIMO-OFDM wireless communication systems, an energy-efficient binary power control with BER constraint (EBPCB) algorithm is proposed based on the power allocation criterion and QoS constraint. Simulations results demonstrate the energy efficiency improvement of EBPCB.

Body Area Network (BAN) consists of various types of small physiological sensors, transmission modules and low computational components and can thus form an E-health solution for continuous all-day and any-place health monitoring. To protect confidentiality of collected data, a shared group key is usually deployed in a BAN, and consequently a secure communication group is generated. In this paper, we propose a bi-directional security and collusion resilience key management scheme for BAN, referred to as FoSBaS. Detailed analysis shows that the scheme can provide both forward security and backward security and resist against collusion attacks. Furthermore, the FoSBaS is implemented on a Sun SPOT based sensor network testbed to evaluate its performance. Experimental results show that a group key can be updated within 102.13 ms with 60.22 mJ energy consumption on a 12 node BAN with 28 bits pairwise key.

In cognitive radio networks, channel aggregation techniques which combine several channels together as one channel have been proposed in many MAC protocols. In this paper, spectrum adaptation is proposed in channel aggregation and two strategies which dynamically adjust channel occupancy of ongoing traffic flows are further developed. The performance of these strategies is evaluated using continuous time Markov chain models. Moreover, models in the quasi-stationary regime are analyzed and the closed-form capacity expression is derived in this regime. Numerical results demonstrate that the capacity of the secondary network can be improved by using channel aggregation with spectrum adaptation.

How to discover a captured node and to resist node capture attack is a challenging task in Wireless Sensor Networks (WSNs). In this paper, we propose a node capture resistance and key refreshing scheme for mobile WSNs which is based on the Chinese remainder theorem. The scheme is able of providing forward secrecy, backward secrecy and collusion resistance for diminishing the effects of capture attacks. By implementing our scheme on a Sun SPOT based sensor network testbed, we demonstrate that the time for updating a new group key varies from 56 ms to 546 ms and the energy consumption is limited to 16.5 - 225 mJ, depending on the length of secret keys and the number of sensors in a group.

A major challenge for cooperative communication in distributed networks is to coordinate relay transmissions without introducing too much overhead. Targeting a clustered network, we propose a novel cooperative communication scheme including channel quality based relay selection and distributed space-time code allocation in this paper. Both analysis and simulations are carried out to investigate the performance of the proposed cooperative scheme, in terms of packet delivery rate, throughput and energy efficiency, under different channel conditions and network density.

Cooperative MAC protocol design has attracted much attention recently thanks to the development of relaying techniques. In single-relay C-ARQ, the relay selection scheme cannot work efficiently in a dense network, due to high collision probability among different contending relays. In this paper, the throughput performance impairment from the collision is analysed in a typical network scenario. Thereby, we propose an optimized relay selection scheme aiming at maximizing system throughput by reducing collision probability. The throughput performance enhancement by the proposed optimal relay selection scheme is verified by simulations.

Unattended Wireless Sensor Networks (UWSNs) operated in hostile environments face a risk on data security due to the absence of real-time communication between sensors and sinks, which imposes sensors to accumulate data till the next visit of a mobile sink to off-load the data. Thus, how to ensure forward secrecy, backward secrecy and reliability of the accumulated data is a great challenge. For example, if a sensor is compromised, pre-compromise data accumulated in the sensor is exposed to access. In addition, by holding key secrecy of the compromised sensor, attackers also can learn post-compromise data in the sensor. Furthermore, in practical UWSNs, once sensors stop working for accidents due to node crash or battery depletion, all the data accumulated will be lost. To address the challenges, we propose a secure and reliable data distribution scheme in this paper. Detailed analysis shows that our scheme can provide forward secrecy, probabilistic backward secrecy and data reliability. To further improve probabilistic backward secrecy and data reliability, a constrained optimization data distribution scheme is proposed. Detailed analysis and simulation results show the superiority of the proposed scheme in comparison with several previous approaches developed for UWSNs.

This paper proposes a Multi-relay Cooperative Automatic Repeat ReQuest protocol (MC-ARQ) for IEEE 802.11 based wireless networks. The proposed distributed relay selection scheme not only selects the best relays but also solves the collision problem among multiple contending relays, by sorting the relays in the network according to their instantaneous channel quality with the destination node. No prior information or explicit signaling among relay nodes is required. Both analytical and simulation results show that significant benefits can be achieved with the MC-ARQ protocol, compared with both the recently proposed PRCSMA scheme and the original non-cooperative DCF scheme.

In this paper, we propose a novel adaptive cooperative MAC mechanism that is specifically designed for two-hop cooperative communications where source and destination cannot hear each other directly. The proposed scheme employs an efficient adaptive relay selection algorithm such that the number of relay nodes is optimized for each cooperative transmission to maximize cooperation benefits and effectively avoid potential collisions with other transmissions. In order to determine the optimal number of relays we apply a training sequence in Hello message exchange, which provides us with a channel status indicator combining both bit-level and flow-level information. Numerical results show that compared with the original 802.11-based scheme and the static cooperative scheme, reliable transmission, reduced power consumption and significant throughput improvement have been achieved by using our two-hop adaptive cooperative MAC mechanism.

Cooperative communication has emerged as a promising technique to enhance system performance in wireless networks. This paper proposes a contention-based cooperative multiple medium access control protocol by means of multiple retransmissions of the same packet from different relay nodes. The proposed scheme exploits cooperative communication capability not only from time diversity derived from multiple temporal transmissions but also spatial diversity derived from distributed multiple relays. A Markov chain is introduced to analyze the throughput performance of the proposed cooperative scheme. The performance evaluation of the protocol is validated and compared with non-cooperative ARQ protocol in error-prone channels.

Channel hopping based parallel rendezvous multichannel MAC protocols have several advantages since they do not need a control channel, require only one transceiver, and produce higher system capacity. However, channel hopping sequences in existing parallel rendezvous MAC protocols have been designed as irrelevant to channel data rates, leading to under-utilization of channel resources in multi-rate multi-channel networks. Considering that data rates among channels may be different, we propose a dynamic parallel rendezvous multichannel MAC protocol for synchronized cognitive radio networks in which the secondary users adjust their own distinct hopping sequences according to the datarates of the available channels, in a datarate-aware manner. A Markov chain based model has been developed to analyze the aggregate datarate of the proposed protocol. Numerical results show that the proposed method can improve the aggregate datarate significantly, compared with that of the existing parallel rendezvous MAC protocol.

This paper presents two MAC strategies for multi-hop cognitive radio networks in single radio multi-channel cases. Both strategies use one of the idle multiple channels for communication among secondary users, and the network will leave the current channel and jump to another channel as a group if any primary user appears. The first strategy is based on a pre-defined pattern that will always tune to the next available channel when primary user emerges. The second one is based on the concept of connected dominating set in which a backbone is formed in the network in order to keep the continuity of the communication. The strategies are evaluated in both homogeneous and heterogeneous channels by simulations. Numerical results show that higher throughput has been achieved with the first strategy in homogeneous channels but in heterogeneous channels the latter strategy performs much better.

Non line-of-sight (NLOS) propagation in range measurement is a key problem for mobile terminal localization. This paper proposes a low computational residual test (LCRT) algorithm that can identify the number of line-of-sight (LOS) transmissions and reduce the computational complexity compared with the residual test (RT) algorithm. LCRT is based on the assumption that when all range measurements are from LOS propagations, the normalized residual distribution follows the central chi-square distribution while for NLOS cases it is non-central. An optimized procedure to generate the sets of range measurements is adopted and least square (LS) instead of approximate maximum likelihood (AML) is used during the identification of LOS propagations, resulting in reduced computation complexity. Simulation results show that the LCRT can efficiently identify the set of LOS. The correct decision rate is higher than 92% and the variances of results are approaching to the Cramer-Rao lower bound (CRLB) when there are more than 3 LOS propagations.

Cooperative communication has been recently proposed as a powerful means to improve network performance in wireless networks. However, most existing work focuses solely on one-hop source-destination cooperation. In this paper, we propose a novel cooperative MAC mechanism that is specially designed for two-hop cooperation communications where the source node and the destination node cannot hear each other directly. In this case, cooperative communication is operated in a two-hop manner and transmit-diversity is achieved by the reception of the same data packet forwarded through multiple relays towards a single destination. The proposed scheme employs an efficient relay selection algorithm to maximize cooperation benefits and can avoid collision effectively. Numerical results show that compared with the original non-cooperative protocol, significant throughput improvement and access delay reduction have been achieved with our two-hop cooperative MAC mechanism.

Reliable broadcast is an essential functionality for disseminating messages to all nodes in a multi-hop wireless network. Ensuring broadcast reliability while minimizing communication overhead is a challenging task when error-prone links are considered. In this paper, we introduce and analyze techniques to address this challenge, and propose an overall algorithm encompassing a combination of the investigated techniques as an efficient solution for reliable broadcasting in multi-hop wireless networks. Simulations are conducted to validate the analytical results and to further evaluate the performance of the algorithm.