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With the advent of increasingly diverse services, applications, and use cases, the 5G mobility environment is expected to be highly heterogeneous. The distributed mobility management (DMM) is emerging as a promising approach for 5G, which provides decentralized handover and traffic management at the edge of the network. However, in order to meet the disparate mobility needs, the DMM process requires flexible design considerations. This paper presents a novel mobile node (MN) centered, software‐defined networking (SDN)–based flexible mobility management architecture, named adaptive multimode mobility management (A3M), which can adaptively operate in multiple modes. The proposed A3M architecture incorporates a novel handover mode selection phase among the traditional handover phases during which a suitable mode of handover operation is evaluated. This makes the A3M handover process adaptable to the varying mobility requirements of the MN and enables it to provide differentiated handover management for MNs with different mobility profiles. The performance analysis of A3M shows that it offers optimal handover performance in terms of primary handover performance metrics such as session disruption delay, packet losses, and signaling costs, compared to the popular network‐based DMM approaches.

Mobility management in a sliced 5G network introduces new and complex challenges. In a network-sliced environment, user mobility has to be managed among not only different base stations or access technologies but also different slices. Managing user mobility among slices, or inter-slice mobility, motivates the need for new solutions. This article, presented as a tutorial, focuses on the problem of inter-slice mobility from the perspective of 3GPP standards for 5G. It provides a detailed overview of the relevant 3GPP standard principles. Accordingly, key technical gaps, challenges, and corresponding research directions are identified toward achieving seamless inter-slice mobility within the current 3GPP network slicing framework.

High Frequency (HF) communications is widely utilised in military, safety and amateur radio systems. Utilising HF communication channels for TCP/IP is highly constrained due to the characteristics of the channel which are presented as low link reliability, limited bandwidth and high transmission delays. Low link reliability is the effect of error prone behavior of HF channels which are governed by physics and environmental conditions. Various implementations of Wideband HF (WBHF) provide additional bandwidth but the low reliability still pose a challenge for TCP/IP communications. In this paper, we present a novel TCP named HF-TCP which is an enhanced version of the standard TCP to provide better performance on HF communication channels. HF-TCP modifies key parameters of TCP to allow TCP sessions to remain open over an extended period of time while the low-data is transmitted with induced delays. Results from experiments show improvements in transmission success rate of 24 percent over standard TCP which failed to initiate or maintain communication. The proposed HF-TCP is backward compatible with generic Local Area Networks (LAN) and wide Area Networks (WAN).

In this paper, we present and evaluate a novel multilevel hybrid-chaotic oscillator. The proposed generalized multilevel-hybrid chaotic oscillator (GM-HCO) was created by combining a multilevel discrete function generated from user data with a continuous function having a damping factor greater than ln(2) to achieve variable rates and adaptive carrier frequencies. Improved spectral efficiency and lower complexity of the transceiver compared with differentially coherent systems were achieved by multilevel signals at the transmitter and a matched filter at the receiver. An exact analytical solution for the generalized fixed basis function and the impulse response of the matched filter were also derived. The bit error rate (BER) expression of the GM-HCO was derived for two levels. It was found that the noise performance of the proposed system was better than a hybrid chaotic system based on forward time and differential chaos shift keying (DCSK). A comprehensive set of simulations were carried out to evaluate the performance of the proposed system with chaotic communication systems in the presence of additive white Gaussian noise (AWGN). The performance of the proposed system was comparable with that of conventional communication systems. The results demonstrate that the proposed system can offer better noise performance than existing chaotic communication systems, and it also offers variable transmitter frequencies and improved spectral efficiency. Noise-like behavior of the chaotic signals provides an additional layer of security at the physical layer compared with conventional (sinusoidal) communication systems.

In multi-user multiple input multiple output orthogonal frequency division multiplexing (MU- MIMO-OFDM) downlink system, it is important to have accurate channel state information (CSI) at the base station (BS) in order to minimize the inter-user interference (IUI). However when the channel changes rapidly, the available CSI at the BS can be outdated and this leads to the performance loss. The channel prediction algorithms can be used to predict the future CSI and compensate for the discrepancy between the estimated channel and the actual channel, and improve the performance of the overall system. In this paper, we propose to use recursive least square (RLS) algorithm to predict the CSI for the upcoming frame in MU-MIMO-OFDM downlink system. The simulation results show that RLS algorithm outperforms the other prediction algorithms such as normalized least mean square (NLMS) and the conventional linear extrapolation method. The simulation results are further validated with the measured channel results.

Road situation awareness plays an essential role in road safety where the emerging Vehicle-to- Infrastructure (V2I) communications are used to issue safety messages to enable awareness among users. It is generally agreed the 4G mobile broadband services can support such V2I road applications. However, how well 4G mobile services can meet the requirements is less understood. In this paper, we propose 4G based V2I road data communication mechanism supporting publish- subscribe paradigm to multicast road safety messages according to the user location. In fact, we introduce advanced filtering method based on the travelling road and the heading direction of the users to filter the most relevant road events, not only limited to the conventional proximity based filtering. Thus communicating road event notifications to the most relevant road users through an infrastructure-less decentralized application layer system is the main focus of our work. A prototype system called "CoRES: Cooperative Road Event Sharing app" is developed to evaluate the approach using an actual on-the- road experiment showing that users can receive reliable notifications at low latency and high reliability.

We proposed several energy-efficient resource allocation algorithms for the downlink of an orthogonal frequency-division-multiple-access (OFDMA) based femtocell heterogeneous networks (HetNets). Heterogeneous QoS and fairness in rate are investigated in the proposed resource allocation problem. A dense deployment of femtocells in the coverage area of a central macrocell is considered and energy usage of both femtocell and macrocell users are optimized simultaneously. We aim to maximize the weighted sum of the individual energy efficiencies (WSEEMax) and the network energy efficiency (NEEMax) while satisfying the following: (1) minimum throughput for delay-sensitive (DS) users; (2) fairness constraint for delay-tolerant (DT) users; (3) required constraints of OFDMA systems. The problem is formulated in three different forms: mixed 0-1 integer programming formulation, time-sharing formulation and sparsity-inducing formulation. The proposed resource block (RB) and power optimization problems are combinatorial and highly non-convex due to the fractional form of the objective function, the integer constraint of OFDMA RBs and non-affine fairness. We adopt the successive convex approximation (SCA) approach and transform the problems into a sequence of convex subproblems. With the proposed algorithms, we show that the overall joint RB and power allocation schemes converge to suboptimal solutions. Numerical examples confirm the merits of the proposed algorithms.

The emerging mobility management schemes for the fifth generation (5G) of mobile networks mostly follow the network-based protocol principles, which do not involve the mobile node (MN) in their operation. Such solutions have not been able to meet the ultra-low handover latency requirement in complex mobility scenarios in 5G. These objectives can be potentially achieved through increased involvement of MN in the handover operation, which can now be conveniently effectuated through virtualization technologies. In this regard, the classical host-based Fast Handovers for Mobile IPv6 (FMIPv6) protocol has the potential to offer several benefits due to its distinctive features, such as link-layer assistance for handover preparation, in-advance new care-of address formulation, and buffering services. Several enhancements to the FMIPv6 protocol have also been proposed, which improve its handover performance. Many of these enhancements focus on the baseline FMIPv6 specification, while others aim to enhance its operation by adding support features, such as mobile multicast, vertical handovers, quality of service assurance, as well as security support. Moreover, several enhancements to the access-technology-specific solutions for FMIPv6 have also been proposed. This paper aims to provide a systematic review of FMIPv6 enhancements in order to gain insight into its advantages as well as its shortcomings. Based on the review, this paper also discusses the evolution prospects of FMIPv6 toward 5G. Finally, some of its potential limitations along with possible research directions in the context of 5G are also indicated.

The channel state information (CSI) at the base station (BS) in multi-user multiple-input multiple-output (MU-MIMO) downlink system can provide a significant performance enhancement in terms of data transmission rate and interference reduction. However due to the time varying nature of the channel the available CSI at the BS can be outdated and this leads to the performance loss. This paper provides an analysis of the effect of outdated CSI on MU-MIMO downlink system when mobile stations (MSs) experience different speeds and how the channel prediction algorithms can be used to compensate for these delays in the time-varying channel. The simulation results show that even few samples delay can have a profound effect on bit error rate (BER) performance in MU-MIMO downlink system and the channel prediction algorithms can be used to compensate these delays to improvise the performance. For the first time, we propose to use normalized least mean square (NLMS) and recursive least square (RLS) adaptive filters for predicting the channels in MU-MIMO downlink system. Compared to the conventional linear extrapolation channel prediction method, both NLMS and RLS provided better performance, with RLS performing better with an increased computational complexity.

One of the principal thrusts of proposed 5G networks is the provisioning of mixed services or heterogeneous Quality-of-Service (QoS) which includes delay-sensitive (DS) and delay tolerant (DT) services. Guaranteeing the fairness in data rate among end-users in such a complex network brings many challenges. In this paper, we consider heterogeneous QoS and fairness in the problem of spectrally efficient resource allocation in OFDMA based 5G heterogeneous networks (HetNets) with femtocells. We aim to maximize the total capacity of all femtocells while satisfying the following: fairness constraint for DT users, minimum throughput for DS users, cross-tier interference threshold of femtocell HetNets and exclusive property of OFDMA subchannels. The formulated problem is combinatorial and non-convex due to the integer constraint of OFDMA subchannels and non-affine equality constraint of the fairness. To make the problem more tractable, we propose to maximise the overall throughput over instantaneous data rate instead of power and subchannel. By doing this, the fairness equality becomes affine on instantaneous data rate. The feasible domain of the problem is redefined with the constraints of subchannels readily included. The transformed problem takes the standard convex form which is much simpler and is easily solved using the Lagrangian dual method. The proposed algorithm has a low complexity and provides a higher spectral efficiency compared to existing algorithms.

Recent advances in chaotic communications have paved the way for the implementation of matched filter based receivers to detect chaotic signals generated by hybrid-chaotic oscillators. These oscillators offer an exact analytic solution given their fixed basis function. This paper extends the hybrid chaotic oscillator concept and presents a novel hybrid-chaotic oscillator for multilevel chaotic modulation. This is created by combining a data dependent discrete system and a continuous chaotic system with a novel damping factor approach to achieve variable rates. Lower complexity is achieved by multilevel modulation at the transmitter and a matched filter at the receiver. An exact analytic solution for the output of the matched filter was also derived. A comprehensive set of simulations were carried out to evaluate the performance of the novel system in Additive White Gaussian Noise (AWGN) channels and to compare it with that of conventional communication systems. The results demonstrate that the proposed system can realize multi-level chaotic communication system with acceptable bit error rate performance.

This paper proposes a key reconciliation mechanism using Reed Solomon code to improve the effectiveness of secret key generation based on Received Signal Strength (RSS) variations in a wireless channel between two communicating parties. We use a two threshold quantization algorithm which can operate as a lossless system improving the secret bit extraction rate. We present our Reed Solomon (RS) code based algorithm for reconciling the independently derived secret keys through sharing of only the syndrome bits. We evaluate our reconciliation algorithm using simulated channel measurements and real environment data gathered between an unmanned aerial vehicle (UAV) and a controller in a semi mobile environment. We show that by selecting appropriate parameters of the RS code, it is possible to generate matching keys at the transmitter and the receiver which can be used to secure the communication at wireless PHY or upper layers.

In this paper, we improve throughput performance of a cognitive radio network through a proposed dual-level sensing strategy. Throughput performance of secondary users cannot be enhanced while providing higher priority to protect primary users from secondary user interference. Therefore, we propose a novel multiple access scheme based on dual-level sensing strategy by which both the interference protection and the throughput enhancement can be accomplished. We propose a dual-level sensing regime within the short sensing period to explore higher transmission opportunities and then utilize the sensing outcome to reduce the collision during the multiple access phase. Performance evaluation shows that the proposed scheme improves the throughput of the secondary users and guarantees the primary user protection during multiple access.

In this work, we study a practical resource allocation (RA) scheme that considers heterogeneous services in OFDMA femtocell networks. Heterogeneous services include guarantees of the minimum data-rate for delay-sensitive (DS) users and the fairness for delay-tolerant (DT) users. The RA problem is formulated to maximize the total throughput of all femtocells while satisfying the constraints of cross-tier interference and heterogeneous services. To tackle this issue, we solve the problem in three steps. First, we relax the fairness constraint of DT users by introducing a new relaxation coefficient. Then, the relaxed problem is addressed by using the Lagrangian dual method. Finally, we develop an iterative algorithm for joint power and resource block (RB) allocation. The proposed scheme outperforms existing methods in terms of the complexity and the total achievable throughput.

An optimal cooperation strategy, decode-to-cooperate, is proposed and investigated for performance improvements in dual-hop wireless relay networks. Based on decode-and-forward (DF) strategy with multiple relay selection, we design a novel scheme such that the source node keeps transmitting sequentially and the selected relays cooperate by transmitting the decoded signal using distributed Alamouti coding. We exploit the multipath propagation effect of the wireless channel to achieve lower probability of error and introduce optimum power allocation and relay positioning. We analyze the scenario when the source to destination direct link is not available and derive a closed form expression for symbol error rate (SER), its upper bound and an asymptotically tight approximation to exploit the performance gain by selecting the optimum relays in a multiple-relay cooperation scheme. Moreover, asymptotic optimum power allocation (based on the SER approximation) and optimal relay positioning are also considered to further improve the SER. The proposed relay selection scheme outperforms cooperative (DF) and non-cooperative schemes by more than 2 dB.

The demand for assistive living technologies is rising rapidly due to the increasing ageing population around the world. Advancements in wearable device technologies have paved the way to patient-centred ubiquitous health monitoring at home. Despite the increasing availability of continuous patient monitoring by integrating various sensors and Body area networks (BAN), little work has focused on automated intervention at multiple levels. On the other hand, certain personal medical treatment devices such as insulin injectors and pneumatic compression therapy devices provide treatment without overall personal health monitoring. In this research, we propose a framework to enable continuous monitoring and control of a personal treatment device seamlessly. Proposed framework assimilates inertial sensor-based activity recognition, intelligent control algorithms, and BAN in a modularised hardware architecture. Consequently, the proposed system can monitor activities of daily living and provide automated intentions. The modularised hardware architecture facilitates the use of single sensing and controller platform for multiple treatment devices. We validate the proposed framework by implementing and testing a prototype automated compression therapy device.

Cooperative communication can attain lower error probability in wireless networks by exploiting the inherent broadcast nature and taking advantage of multi-path propagation. In order to leverage performance gains achieved by virtual multiple- input multiple-output (MIMO) systems, we design a novel cooperative protocol, Decode-to-Cooperate (DCOOP). We evaluate its performance on a testbed implemented on Universal Software Radio Peripheral Reconfigurable Input/Output (USRPRIO) platform. The main challenge during the testbed deployment was to consider transmission under tightly synchronized nodes in a slow fading environment. Extensive experiments were performed to evaluate the performance of the testbed and the results show that it can operate at lower transmit power and increase the coverage area for a desired bit error rate (BER).

Dispersing a data object into a set of data shares is an elemental stage in distributed communication and storage systems. In comparison to data replication, data dispersal with redundancy saves space and bandwidth. Moreover, dispersing a data object to distinct communication links or storage sites limits adversarial access to whole data and tolerates loss of a part of data shares. Existing data dispersal schemes have been proposed mostly based on various mathematical transformations on the data which induce high computation overhead. This paper presents a novel data dispersal scheme where each part of a data object is replicated, without encoding, into a subset of data shares according to combinatorial design theory. Particularly, data parts are mapped to points and data shares are mapped to lines of a projective plane. Data parts are then distributed to data shares using the point and line incidence relations in the plane so that certain subsets of data shares collectively possess all data parts. The presented scheme incorporates combinatorial design theory with inseparability transformation to achieve secure data dispersal at reduced computation, communication and storage costs. Rigorous formal analysis and experimental study demonstrate significant cost-benefits of the presented scheme in comparison to existing methods.

Concept inventory tests are one method to evaluate conceptual understanding and identify possible misconceptions. The multiple-choice question format, offering a choice between a correct selection and common misconceptions, can provide an assessment of students' conceptual understanding in various dimensions. Misconceptions of some engineering concepts exist due to a lack of mental frameworks, or schemas, for these types of concepts or conceptual areas. This study incorporated an open textual response component in a multiple-choice concept inventory test to capture written explanations of students' selections. The study's goal was to identify, through text analysis of student responses, the types and categorizations of concepts in these explanations that had not been uncovered by the distractor selections. The analysis of the textual explanations of a subset of the discrete-time signals and systems concept inventory questions revealed that students have difficulty conceptually explaining several dimensions of signal processing. This contributed to their inability to provide a clear explanation of the underlying concepts, such as mathematical concepts. The methods used in this study evaluate students' understanding of signals and systems concepts through their ability to express understanding in written text. This may present a bias for students with strong written communication skills. This study presents a framework for extracting and identifying the types of concepts students use to express their reasoning when answering conceptual questions.