Compared with passive flow correlation technologies based on flow characteristics, network flow watermarking, a kind of active flow correlation technology, is characterised by high accuracy, low false positive rate and short observation time. The basic framework and main elements of flow watermarking are formally described. The robustness and invisibility focused by flow watermarking as well as typical application scenarios (such as stepping-stone traceback, anonymous abuser correlation) of flow watermarking are expounded. The intra-flow and inter-flow interferences (such as repacketisation, packet reorder, delay normalisation, flow mixing, flow splitting and flow merging) faced by flow watermarking are briefly introduced. Analysis and comparison on different watermark carriers (packet payload, traffic rate, packet timing, packet number, packet length, packet order and hybrid carrier) based typical flow watermarking technologies, including flow fingerprinting technologies, are conducted, then, a review on security threats faced by flow watermarking, including multi-flow attack, mean-square autocorrelation attack, Kolmogorov–Smirnov test, BACKLIT detection and replication attack, and main countermeasures for increasing invisibility of flow watermarking is carried out. Current research hotspots and future development trends of flow watermarking are summarised and prospected from the aspects of architecture design, invisibility enhancement, adaptive capability improvement, performance evaluation, deployment and application.

Mitigating the effect of fading in wireless networks has been a prominent benefit associated with cooperative relaying. Especially in multi-relay scenarios, efficient resource allocation can drastically improve the performance of cooperative systems affected by fading. However, practically, a relay may not cooperate unless provided with some incentive to improve its utility. To address the above problem, this study introduces a novel integrated game-theoretic framework which involves incentive-based optimal power allocation. Coalition formation game has been used to model the cooperation among relays which is integrated into a Stackelberg game, for considering the benefits of source and relays jointly. The game-theoretic framework has been implemented for both disjoint and overlapping coalitions with an objective to find an optimal and stable overlapping coalition set of relays. This not only maximises their utilities, but also helps the source to allocate the optimal power to the relays at the optimal price, thereby, increasing its own utility. Simulation results have confirmed that the proposed game-theoretic solutions achieve comparable performance in terms of system throughput when compared with the centralised approach. In particular, overlapping coalition approach exhibits consistently better performance than the disjoint coalitions approach due to increased power allocation to individual relays.

In this study, a closed-form solution is presented for the constrained water-filling problem (CWFP) where in powers allocated to the user resources maximise the user's capacity under an interference constraint and a total power constraint. Total power constraint in CWFP is to save the energy in wireless network. To solve CWFP, erstwhile algorithms compute powers for all the resources iteratively. Unlike existing algorithms, the proposed method calculates the number of resources that gets positive (or non-zero) powers using the concepts of traditional water-filling problem. Later, powers are allocated to the resolved resources (that gets positive powers) alone using the closed-form solution, which reduces the number of computations. It can be discerned that the computational complexity of the given solution is of the order of , where is the total number of resources; which is remarkably lower than that of the prior algorithms specified by an order of .

NAND flash memories, due to their several advantageous characteristics, have recently dominated the data storage industry and its global market. Currently, multi-level cell memories, in which each cell can store more than one bit of data resulting in higher data storage capacities, have gained a considerable amount of research interest. However, this comes at the cost of several limitations and increased performance degradation. Various studies have shown that among several error sources in multi-level cell memories, inter-cell interference is the most significant one. Therefore, to mitigate the devastating effect of the interference, simple, feasible, and yet efficient equalisation techniques become essential for achieving desired data reliability. In this study, first, a thorough analysis on deriving the distribution of the interference-free and interference-affected data is carried out. Then, novel low-complexity equalisation methods are proposed, and their beneficial complexity-performance trade-offs compared with the existing techniques are illustrated. Finally, simulation results are presented to show that the proposed algorithms considerably improve the error performance, while maintaining the low-complexity constraints.

As a promising interference management technique, interference alignment (IA) was proposed for improving system capacity and spectral efficiency by precoding and filtering design. However, the previous works assumed the equal power allocation among data streams in IA-based networks, and the sum-rate may fall short of the theoretical maximum without the energy-efficient optimisation. In this study, a novel approach (two-game theoretic) is presented, to solve the rate maximisation problem in the IA-based uplink multiple-input multiple-output cellular networks. First, a two-game analytical framework is presented, where the IA design and power allocation are modelled as two game processes, respectively, and the authors prove that both games have Nash equilibrium solutions. Second, based on the framework, two iterative algorithms of joint IA and power allocation that achieve the maximum sum-rate are proposed. In addition, the authors analyse the sum-rate performance loss under imperfect channel state information (CSI), which depends on the variance of CSI error. Simulation reveals that the sum-rate performances of the proposed iterative algorithms are higher than that of the previous schemes at low signal-to-noise ratio, whose computational complexities are acceptable.

This study introduces a novel framework and analysis tool to monitor the evolution of the ripple size during the Luby-transform (LT) decoding process. It provides a closed-form probability expression to statistically describe the behaviour of the ripple size at each step of the decoding. The probability function is conditioned on the size of the ripple in the previous step, the number of recovered source symbols and the encoded symbols' degree distribution. The authors further derive a closed-form expression for the ripple size after new encoded symbols are received by a decoder with an empty ripple. This relates to the activation of belief propagation decoding attempts once premature terminations occur. They validate their analyses through numerical examples of an LT-coded system. The results show that their analyses precisely coincide with the numerical results.

In this study, the authors investigate the effect of the measurement error on the performance of the pilot-based power allocation of the wireless backhaul for the heterogeneous mobile femtocell networks. To implement the pilot-assisted power allocation, it is essential to measure the received power on the backhaul. However, due to the dynamic feature of the wireless backhaul, the perfect measurement is approximately impossible in practice. Moreover, in spite of the signal to interference plus noise ratio (SINR) balancing, the pilot-assisted power allocation is significantly sensitive to the measurement error. Accordingly, we specifically evaluate the effect of the measurement error of the uplink received power in the macro base stations on the performance of the pilot-assisted power allocation in terms of the SINR balancing and the outage probability of the mobile femto base stations at the convergence point. Then, a minimum mean-squared error (MMSE)-based approach is proposed to mitigate the effects of the measurement error. Analytical and simulation results demonstrate that the SINR balancing is degraded when the measurement error on the backhaul link is increased. Also, the effectiveness of the MMSE-based approach under the imperfect measurement condition is denoted in terms of the SINR balancing especially in high measurement error.

A new approximate expression for the probability density function (pdf) of K-distribution is proposed. The approximate pdf is found to be in good agreement with the exact analytical closed-form expression over the desired range of scintillation index lying between 2 and 3. Employing the proposed pdf, the expression in respect of two of the QoS measures of fade probability and bit error rate (BER) valid under various modulation schemes is given. Using the generalised expression of BER, plots under ON–OFF keying and binary phase shift keying modulation schemes are shown. The resulting expressions provide a better understanding in contrast to the exact results obtained in terms of Meijer G functions. Numerical computations are carried out to demonstrate the efficacy of approximate results.

Recently, physical layer authentication techniques are emerging to detect spoofing attacks in wireless networks based on high consistency between two legitimate successive channel information. However, this high consistency is not always available, especially in dynamic networks, such as mobile scenarios. In this study, the authors propose a physical layer spoofing detection scheme based on sparse signal processing that exploit sparse representation and Savitzky–Golay filter, and use machine learning strategy to improve the spoofing detection accuracy under the case of low channel consistency. Simulation results show that the proposed technique can significantly improve the detection accuracy under the condition of low channel consistency.

This study presents an improved channel estimation method for orthogonal frequency division multiplexing (OFDM) over doubly-selective channels. Channel variation has been approximated by the basis expansion model using a specific comb-type pilot approach. Since the data are transmitted as successive symbols in OFDM systems, the authors derive a channel estimation technique exploiting the additional information provided by adjacent symbols pilots. The main idea of the proposed method is to reduce the pilots to useful data ratio in order to improve the effective throughput and to increase the model accuracy in high mobility situations. The proposed algorithm has been investigated by considering both the conventional linear minimum mean square error and the least squares estimator. Various simulations have been conducted by considering different pilot rates with high Doppler effects and additive white Gaussian noise. The obtained results, in terms of the mean square error and binary error rate, show that the proposed algorithm outperforms the conventional techniques which are based on comb pilot-assisted estimation.

The filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) has aroused widespread concern in the 5G communication. However, FBMC-OQAM has an inherent drawback of high peak-to-average power ratio (PAPR) that should be mitigated. Here, the authors propose an efficient hybrid scheme based on sparse partial transmit sequence (sparse PTS) scheme and tone reservation (TR) scheme to reduce the PAPR in FBMC-OQAM systems. The first step is to detect and record the location of peak of FBMC-OQAM signals and adopt phase rotation factors (based on PTS) to directly optimise the phase of recorded peak signals, which is called sparse PTS. Then the result is further processed by TR scheme for PAPR reduction. Simulation results show that the proposed hybrid scheme provides better PAPR reduction performance than the two schemes, and can achieve less side information transmitted than the sparse PTS scheme.

Caching at the user devices is a key technology to alleviate backhaul load and improve users' quality of experience in mobile edge networks. However, due to the concern of privacy and limited battery life, users are not willing to share their resources. In this study, the authors jointly design the caching strategy and incentive scheme to encourage the users to share their storage resources and improve the social welfare of the cellular network. First, the user equipments (UEs) are classified into different types according to their preference to share cache resources. Then, based on contract theory, an optimisation problem with necessary constraints is formulated aiming at maximising the base station (BS)'s utility. The reward the BS pays for a UE is based on the total amount of contents it shares with other UEs, which is related to the caching policy of UEs. A heuristic caching strategy is proposed and the optimal contract is obtained. Finally, the system performance of the proposed solution is analysed, simulation results show that the incentive scheme can improve the willingness of users to share contents, and the proposed caching strategy contributes more to the social welfare compared with two baseline caching schemes: fair caching and random caching.

Filter cascading effects are identified and compensated in flexible coherent multi-carrier optical networks using, for the first time, a complex-valued support vector machine (C-SVM) non-linear equaliser which is compared to phase-conjugated subcarrier-coding (PC-SC)-based non-linearity compensation. The transmission performance of super-channel-based dual-polarisation coherent multi-band optical OFDM (DP-MB-OFDM) is analysed in a flexible network with two-stage wavelength selective-switch reconfigurable optical add-drop multiplexer for coarse and fine switching granularity. It is shown that filter cascading effects have significant impact only on edge OFDM sub-bands. On the other hand, C-SVM outperforms PC-SC resulting in an extension of the transmission-reach, for instance, by 420 km when employing 32-quadrature amplitude modulation at a targeted bit-error-rate of 10⁻³. This occurs since C-SVM can compensate more effectively stochastic-induced nonlinear cross-talk effects. Moreover, the interplay between polarisation-mode dispersion (PMD) and fibre non-linearity is also investigated in DP-MB-OFDM, revealing that a high PMD causes time fluctuation on the non-linear interaction affecting the balance of the ‘twin-subcarriers’ in PS-SC.

In order to reap the full scale of benefits of millimetre wave (mmWave) massive multiple-input multiple-output (MIMO) systems, the design of antenna arrays at the transmitter or receiver becomes more critical due to the propagation characteristic at mm-frequencies. In this study, the authors investigate the performance of two types of antenna array, namely uniform rectangular planar array (URPA) and uniform cylindrical array (UCYA). The channel behaviour is presented in full-dimensional mmWave propagation conditions by considering both the azimuth and elevation dimensions. The squared inner product and singular value spread are studied for URPA and UCYA configurations, these properties reveal the effective interference and channel's stability of antenna array. The authors also evaluate the achievable rate with the equal power allocation and water-pouring power allocation schemes. Simulation results show that under the same system configurations, the performance that includes the radiation pattern, the channel eigenvalue distribution, the effective interference, and the achievable rate, of UCYA configuration always outperforms that of URPA configuration. Therefore, it can be concluded that in three-dimensional propagation environments, the UCYA configuration is especially appealing for mmWave MIMO systems.

Reducing energy consumption of the internet becomes more and more important. The authors propose a novel approach, called predictive energy-saving approach (PESA), to put near-idle nodes of a network into sleep mode to save energy. In PESA, they propose an online spatial hidden Markov model (OSHMM) to describe the distribution of the network traffic and predict the lowest-loaded nodes. Those nodes will be put into sleep mode under the constraints that the network's full connectivity is kept and no new congested nodes are generated. To reduce the computation, they leverage on an online training technique and M-algorithm in OSHMM. They evaluate the approach over a randomly generated topology and a real ISP backbone topology with a real traffic dataset. The results show that the proposed approach is energy efficient with low computation complexity.