This study addresses the training sequence design problem for multipath channel estimation in faster-than-Nyquist (FTN) system. The authors process the estimation in the frequency domain and give the search criterion which is only the function of the power spectrum of the training sequence. The optimal sequence according to this criterion is found by using search strategy described in detail in this study and the performance of it is tested by Monte Carlo simulation.

The problem of relay selection in amplify-and-forward (AF)-based hybrid satellite-terrestrial cooperative communication systems is considered. A partial relay selection scheme is studied in which satellite selects a relay earth station (ES) among multiple relay ESs (situated on ground) on the basis of maximum instantaneous signal-to-noise ratio (SNR). Satellite-relay ESs are assumed to follow Shadowed-Rician fading, whereas relay ESs-destination ES links (terrestrial links) are assumed to follow Nakagami-m distribution. First, the cumulative distribution function and probability density function (PDF) of the maximum instantaneous SNR of satellite-relay ESs links are derived; then by using this PDF, the expression of moment generating function (MGF) of the received instantaneous SNR at destination ES is obtained. The average error performance of the considered system with the proposed relay ES selection is derived in terms of Meijer-G functions by using MGF approach. In order to get the diversity order of the relay ES selection-based AF scheme, the asymptotic PDF of the considered scheme is derived, and then by using this asymptotic PDF, the analytical diversity order of the system is obtained. It is demonstrated by the analysis and simulation that the performance of the AF-based hybrid satellite-terrestrial communication systems can be significantly improved by deploying more relay ES at the ground in between satellite and destination ES.

Efficient use of available energy resources for real-time multimedia communication with a quality guarantee is one of the main challenges for future mobile computing systems. To meet the high quality-of-experience (QoE) demand of multimedia services, we propose a novel quality-driven joint source-channel coding (JSCC) scheme with an unequal error protection (UEP) technique that allocates bits by optimising source intra refreshing rates and channel correction coding rates. The key contribution of this work is that the frame importance diversity at the application layer is jointly considered with the error correction techniques and resource constraints at lower layers. For any given bit budget, the JSCC model is capable of allocating adaptive bits between source coding and channel coding among media streams. The source-aware UEP scheme is capable of dynamically allocating the error correction bits among frames, achieving the maximum overall QoE. Simulation results demonstrated that significant improvement in multimedia quality and remarkable energy/time conservation can be achieved by deploying the proposed group-based JSCC strategy, although the complexity is limited.

The performance of low-density parity-check (LDPC) code is analysed in the frequency hopping (FH) system with partial-band interference (PBI). Both of Slow Frequency hopping (SFH)/binary phase-shift keying (SK) and Fast Frequency hopping (FFH)/binary frequency-SK schemes are considered in which the channel fading and diversity combining are involved, respectively. The symmetry conditions on PBI channel are proven, and then the probability densities of initial message for sum–product decoder are derived. Given a probability of hopping to a jammed state, the decoding thresholds of LDPC codes on PBI channel are obtained using density evolution, which are in good agreement with the simulation results. Furthermore, the irregular LDPC codes are optimised over PBI channel, and the simulation result shows that it has better anti-jamming performance than the existing regular and irregular codes which have been employed in FH systems.

Millimeter wave (mmWave) communications have been considered as a key technology for future 5G wireless networks since it can provide orders-of-magnitude wider bandwidth than current cellular bands. To overcome the severe propagation loss of the mmWave channel, an economic and energy-efficient analogue/digital hybrid precoding and combining transceiver architecture is widely used in mmWave massive multiple-input multiple-output (MIMO) systems. The digital precoding/combining layer offers more freedom than pure analogue one and enables multi-stream transmission. In this study, the authors consider the problem of codebook-based joint hybrid precoder and combiner design for multi-stream transmission in mmWave MIMO systems. The authors propose to jointly select an analogue precoder and combiner pair for each data stream successively, which can maximise the channel gain as well as suppress the interference between different data streams. Then, the digital precoder and combiner are computed based on the obtained effective baseband channel to further mitigate the interference and maximise the sum-rate. Both fully-connected and partially-connected hybrid beamforming structures are investigated. Simulation results demonstrate that the proposed algorithms exhibit prominent advantages in combating interference between different data streams and offer satisfactory performance improvements compared with the existing codebook-based hybrid beamforming schemes.

Here, the authors develop a method of simultaneous optimisation of precoder and equaliser for the multi-user multiple-input multiple-output (MIMO) system by minimising outage probability. In order to do that, the authors first characterise the signal-to-interference-plus-noise ratio of downlink multi-user MIMO system in the presence of both multi-user interference and self-interference. The closed-form expression for the outage probability is derived in terms of the eigenvalues of an indefinite weight matrix of a quadratic norm. Next, the authors develop an active-set algorithm-based precoder and equaliser by minimising the derived outage probability expression. This work investigates the effect of various system parameters such as the number of users, the number of multi-path channels, the number of transmitting and receiving antenna elements, and the additive noise variance on the outage probability and bit error rate. Simulation results validate the theoretical analysis for multiple system configurations. Lastly, the authors show that the designed precoder and equaliser improves the overall system performance.

With the long propagation delay of an acoustic signal in underwater communications systems, relay node selection is one of the key design factors, because it significantly improves end-to-end delay, thereby improving overall network performance. To this end, the authors propose orthogonal frequency division multiplexing-based spectrum-aware routing (OSAR), a scheme in which spectrum sensing is done by an energy detector, and each sensor node broadcasts its local sensing results to all one-hop nodes via an extended beacon message. Each sensor node then selects nodes that agree on an idle channel, consequentially forming a set of neighbouring nodes. The selection of a relay node is determined by calculating the transmission delay – the source/relay node selected is the one that has the minimum transmission delay from among all nodes in the neighbouring set. To evaluate OSAR, the authors perform extensive simulations via ns-MIRACLE for different numbers of channels using a BELLHOP model, and evaluate the average delay for different sensor nodes within the considered network. The results show a substantial decrease in delay as the number of sensor nodes increases in the network. In addition, the authors verify that the packet delivery ratio increases with increases in the number of sensor nodes, and prove better performance in the overhead ratio. The authors' simulation results verify that OSAR outperforms existing solutions.

In this study, a spectral efficient channel recovery scheme is proposed for spatial-temporal correlated sparse massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing systems. By exploiting the spatial-temporal correlations of massive MIMO channels, superimposed time-frequency training sequences (TSs) are jointly utilised for accurate channel state information (CSI) acquisition. Moreover, a novel time-frequency TS pattern design scheme is proposed to improve the recovery performance based on structured compressive sensing theory. Furthermore, the discrete prolate spheroidal basis expansion model of massive MIMO channels in the space-domain is utilised to reduce the frequency-domain pilots overhead and improve the spectral efficiency. Simulation results show that the proposed scheme could achieve accurate CSI with great improvement in spectral efficiency and computational complexity.

A Differential quadrature phase shift keying (DQPSK) modulator and demodulator system incorporating surface acoustic wave (SAW) device is presented. The SAW device in the modulator consists of four delay lines corresponding to different phase delays and generates phase shift keyed radio-frequency signals. In the demodulator section, another SAW device performs addition operation between two consecutive received signals to obtain the phase difference. The DQPSK demodulation is extended for the demodulation of quadrature phase shift keying signal without the requirement of locally generated reference carrier. The operation of the proposed DQPSK system using SAW along with the bit error rate (BER) performance is presented. The effect of additional phase delay in the received signal on BER is also presented. Addition operation of the received signals using SAW is also verified using simulation.

In this study, the authors propose a non-parametric algorithm to implement the estimation of transmit-antenna number, which is a prerequisite for blind interception process of multiple-input multiple-output orthogonal frequency division multiplexing signals in frequency selective fading. Specifically, a series of test statistics are constructed by exploiting the eigenvalues of the sample covariance matrices from each subcarrier, followed by a combination of these test statistics. As a consequence, the number of transmit antennas can be determined after a serial binary hypothesis testing. The theoretical analysis and simulation results verify the rapid convergence and high reliability of the proposed algorithm at a relatively low signal-to-noise ratio .

In this study, an integrated scheme is proposed to stream real-time scalable videos from a base station to multiple secondary users over cognitive radio networks. The objective of the proposed scheme is to maintain continuous video playback with acceptable perceptual quality at the secondary users end. The proposed scheme is a channel allocation algorithm integrated with a rate control and scheduling algorithms. The channel allocation algorithm is introduced to optimally assign the available channels among the secondary users while taking into considerations their buffer occupancies as well as the channel qualities as seen by the secondary users to meet the requirements of the real-time streamed videos. While the rate control algorithm adapts the source rate to meet the streaming requirements, the scheduling algorithm splits the transmitted video information based on its importance to guarantee the continuity of video playback. The simulation results do not only demonstrate the efficient utilisation of available resources of the cognitive network by the proposed scheme but highlights a desirable need-based fairness when allocating the available channels between the secondary users. The simulation results also indicate that scheduling the transmitted video information on a window basis outperforms frame-based streaming.

Wireless sensor networks (WSNs) generally comprise a large number of tiny sensor nodes that perform network processing of the acquired data and then forwarding such data to the sink via multi-hop paths. The sensor nodes are resource constrained in terms of battery life, memory, and processing capability. Hence, a critical aspect in WSNs is power scarcity, which directly affects the network operation lifetime and the performance of applications. Furthermore, large-scale WSNs demand a high level of self-organisation so each node of the system autonomously makes decisions. In this respect, self-organising methods enhancing the network lifetime while achieving balanced energy are highly significant in WSNs. In this study, the authors apply gene regulatory network (GRN) principles to WSN system and design a new GRN-inspired model for autonomous node scheduling in WSNs. GRNs have received considerable attention from computational engineering for their robustness, scalability, and adaptability with simple local interactions and limited information. They apply cellular mechanisms of GRNs to WSNs and establish a metaphor between a multi-cellular system and a WSN system. Then, they propose a new model inspired by GRN so each sensor node autonomously schedules its state with local interaction based on sensor variable signalling while achieving the global object predefined by an application or user. Using control theory, they analyse system stability and derive steady states of the proposed system. They further derive the conditions of system parameters to ensure system convergence to a desired state. Simulation and numerical results are evaluated to provide insights into the effect of various system parameters on energy balancing and system stability.

Spinal codes, a new class of rateless codes, have received considerable attention for their capacity-approaching performance over noisy channels. Hash function is the core of a spinal encoder to generate infinite coded symbols, which has higher hardware complexity. In this study, the authors propose a multiplicative repetition-based method instead of the hash function to generate innumerable symbols with low encoding complexity. Furthermore, both frozen-aided and cyclic redundancy check-aided decoding methods are proposed to improve the spectral efficiency. Simulation results show that the proposed spinal codes have lower computational complexity and can achieve higher spectral efficiency in the high signal-to-noise ratio region compared with the conventional ones over both additive white Gaussian noise and Rayleigh fading channels.

Massive multiple-input multiple-output (MIMO) transmission/reception is a very promising enabling technique for future cellular systems. The performance of massive MIMO systems relies on the availability of channel state information (CSI) at the transmitter. However, due to estimation errors and delay this CSI is imperfect. Additionally, the use of many radio frequency (RF) chains to drive a large number of antennas at the transmitter quickly becomes impractical when that number increases. Thus, reducing the number of RF chains in massive MIMO systems is essential in order to reduce the system complexity and cost. Considering a massive MIMO system with a single-RF-chain transmitter, in this study, the authors design a precoding technique that is robust to the channel uncertainty. To reflect realistic restrictions in the authors' design, they consider the peak total transmitted power rather than the average power constraint. Also, they consider imperfect CSI and model the uncertainty region as a bounded one, which is a reasonable assumption. In this transmitter structure, there is only one power amplifier and load modulation rather than voltage modulation is used to generate the desired signals on the antenna elements. They demonstrate that when a very simple fixed equaliser is used at all user terminals, the problem of minimising the mean-square error of the received signals at user terminals under the worst-case channel uncertainty can be transformed into a convex optimisation problem. They provide simulation results and demonstrate that the proposed robust precoding technique outperforms non-robust techniques in terms of power efficiency and signal-to-interference-plus-noise ratios.

Consider an underlay cognitive radio network where an eavesdropper (Eve) targets to intercept the information exchanging between the primary nodes. The secondary system is allowed to access the licensed spectrum as long as it does not violate the target quality-of-service (QoS) of the primary network. In return, the secondary network also assists the primary network against the malicious attack of the Eve. The authors aim at designing a resource allocation algorithm maximising the secrecy rate of the primary system while also satisfying the QoS requirement of the secondary system. To be more precise, a jamming noise accompanied by the information signal to degrade the Eve's channel and the information beamforming vector at the secondary transmitter is jointly optimised. The problem of interest is formulated as a non-convex optimisation problem. For the case in which global channel state information (CSI) is available, the authors propose a path-following algorithm which aims at locating a Karush-Kuhn–Tucker solution to the original non-convex program. By novel transformations and approximations, the authors arrive at only a simple convex problem of moderate dimension. For the case in which only statistics of the Eve's CSI are available, the authors reformulate the considered problem by replacing a non-convex probabilistic constraint with a set of convex constraints. A worst-case scenario for a secure communication, where an optimal linear decoder is used at the Eve, is also considered. The superior performance of the proposed design is revealed by numerically comparing it with other known solutions.