Sparse code multiple access (SCMA) is a promising candidate air interface of the next generation mobile networks. However, the decoding complexity of current message passing algorithm for SCMA is very high. In this study, the authors map SCMA constellation to q-order Galois field () and introduce a trellis representation to SCMA. Based on the trellis representation, they propose low-complexity decoding algorithms for SCMA by using truncated messages, which is referred as extended max-log (EML) algorithm. As the truncated length of EML is unitary for each user, they further propose a channel-adaptive EMLalgorithm to truncate the messages with a rule that can be adaptive to the channel state. Simulation results show that the proposed schemes obtain a low computational complexity with only a slight performance degradation when the truncated length is selected appropriately.

In adaptive diffusion networks, one of the main challenges is the large volume of data exchange among nodes needed to arrive at a collective decision. In this study, a new model for adaptive diffusion networks is proposed which offers a tradeoff between the mean-square error performance of the system and the volume of data exchanged among network nodes while preserving the network convergence rate. Study of the mean-square stability of the network under the proposed algorithms is provided. Also, a study of the mean-error dynamic behaviour of the network is carried out. A closed-form expression for the overall network steady-state means-square error is derived and verified against simulated data. The proposed algorithm is applied to a cellular network location estimation problem, and delivers good performance even under 75% reduction in data exchange volume.

Wireless body area networks (WBANs) can be widely used in wireless medical, motion detection etc. However, the existence of interference results in the increase in energy consumption and delay. To mitigate interference, nodes are prevented from using the same or similar spectrum resources by adopting multi-channel media access control (MAC) protocols. Here, the authors propose a multi-channel MAC protocol towards energy efficiency and low interference (EIMAC). Firstly, the states of each channel are clarified by the channel mapping mechanism. A novel channel selection strategy, considering the unfairness between high or low priorities, then is carried out. After that, considering the characteristics of node including residual energy, user priority, and data volume, the authors propose a low energy consumption enabled transmission mechanism. Lastly, the authors utilise a novel collision avoidance mechanism to reduce the collision probability of packets. Numerical results show that EIMAC significantly enhance the performance of WBANs in terms of delay, throughput, and energy consumption.

The -norm penalised (LP) normalised least mean square algorithm converges faster than the LP normalised least mean fourth algorithm does, but the latter can achieve better steady-state performance, particularly in regions with low signal-to-noise ratios (SNRs). To simultaneously take advantage of both merits, a sparse hybrid adaptive filtering algorithm is proposed in various SNR environments. Specifically, the authors construct a cost function that uses the statistical error term and sparse penalty term. The first term is designed by a hybrid error function of the second- and fourth-order statistical errors, respectively, and the second term is obtained using a sparse constraint function. The hybrid error term can be easily balanced by a proportional parameter . Moreover, they devise a non-uniform step size in the proposed algorithm to further balance the convergence speed and estimation error. Simulation results are provided to validate the proposed algorithm in various SNR environments.

The continued increase in several mobile applications forces to replace existing limited spectrum indoor radio-frequency wireless connections with high-speed ones. Visible light communication (VLC) is a promising license free indoor wireless technology that could offer high-speed connections. However, both co-channel interference (CCI) from more neighbour transmitters and inter-symbol interferences (ISI) from multipath reflections limit the performance of VLC downlink channel. In this study, a constraint field of view angular diversity receiver (CFOV-ADR) is proposed to mitigate these limitations. By optimising the photodetector's (PD) field of view (FOV) angle, the line of sight CCI could be totally eliminated and the ISI could be significantly reduced. The optimal range for FOV angle is calculated in a typical indoor scenario. Furthermore, the zero-forcing (ZF) algorithm is applied to the conventional ADR (ADR-ZF) which can significantly eliminate the ISI components. The received optical signal-to-interference-plus-noise ratio (SINR) is tested at various room positions. The simulation results show that the proposed CFOV-ADR can achieve higher SINR performance than single receiver, conventional ADR, and ADR-ZF at all positions and orientations.

Free space optical (FSO) communication systems have high bandwidth, cost effectiveness and can provide secure wireless communication service for users. They can also form asymmetric dual-hop cooperative communication links by multiplexing numerous radio frequency (RF) users by using amplify–forward transmissions over the FSO channel after converting to optical signals. In this study, an asymmetric dual-hop RF–FSO system is studied where the RF links follow the well-known Nakagami-m fading distribution and the FSO channel is efficiently modelled by the Málaga turbulence fading. The performance of the system is studied by deriving the closed-form expressions for the outage probability and ergodic channel capacity together with their asymptotic analysis at high signal-to-noise ratio. The numerical results are corroborated by Matlab analytical plots.

Network function virtualisation and software-defined networking are two emerging technologies which together enable a new service provisioning paradigm called service function chain (SFC). However, the SFC should be scalable enough to accommodate one or more service functions joining or leaving it during its lifecycle. In this work, the authors first formulate this problem as an integer linear programming (ILP) model, and then address this ILP model to obtain the optimal solution. Due to the extremely high execution time for solving the ILP model, they next proposed a dynamic heuristic to solve this problem. In particular, the proposed heuristic leverages two kinds of strategies to handle the scale-in (i.e. removing existing service functions from SFCs) and scale-out (i.e. adding new service functions to SFCs) requests. Since each SFC has a corresponding service function path (SFP) constructed, the first kind of strategy proposes to serve the arriving scale-in and scale-out requests based on the in-use SFP, while the second kind of strategy intends to optimise the in-use SFP to achieve low cost and packet loss probability proactively. Finally, the experimental results indicate that the proposed heuristic can achieve better performance than the existing algorithm.

Without channel state information at the users and relay node, a non-coherent transmission scheme for the two-way relaying systems is investigated in this study. At the relay node, the authors first detect the uplink data with non-coherent maximum likelihood receiver by fully utilising the large receiving freedom of relay's large-scale antennas. Channel estimations can also be obtained by treating the detected uplink data as pilot symbols. Then, the relay node forwards the detected data by using beamforming. To assure the reliable detection of the users' transmitted symbols non-coherently, the authors propose a transmitting constellation design with the idea of searching an optimal angle for rotating one user's constellation. Specially, for M-PSK constellations, they derive the optimal rotation angle, which is highly consistent with the exhaustive searching results. In addition, they also analyse the lower bound of channel estimations in terms of normalised mean square error (NMSE). From simulation results, the proposed non-coherent transmission scheme achieves considerable error performance, and the NMSE lower bounds of channel estimations are also tight when the number of relay's antennas approaches to be large.

Companies and developers of emerging Internet-of-Things (IoT) technologies consider Bluetooth low-energy (BLE) standard as a strong candidate to be the backbone of wireless IoT devices and support their low-power requirements. Likewise, the BLE has adopted Gaussian frequency shift-keying (GFSK) signalling due to its power and spectral efficiencies, which are the most fundamental performance criteria for modulation schemes. For this reason, it is worthwhile to research and develop transceivers that maintain these advantages and achieve a low-complexity implementation for the digital modulator and demodulator. Different techniques have been proposed for this purpose, such as hardware usage optimisation, efficient pulse shaping and decomposition of the signal. This study presents a novel linear GFSK demodulator which has the following attractive advantages: low complexity, near-optimal performance in the additive white Gaussian noise channel and the possibility of operating with different GFSK modulators (with a nominal modulation index of 0.5) so it could be applied in BLE devices. In addition, the theoretical error probability is obtained and compared with simulation results.

This study proposes a sparse non-orthogonal frequency division multiplexing (S-NOFDM) based on sparse representation to improve the spectral efficiency of orthogonal frequency division multiplexing (OFDM). The subcarriers of S-NOFDM are generated from a subset of OFDM orthogonal subcarriers, which therefore requires less spectral resource. Each selected OFDM subcarrier is shifted into a group of overlapping subcarriers with different time delays. The modulated signal is produced by solving the sparse representation of the input signal under the generated set of subcarriers. The demodulation is simply a linear combination of generated subcarriers with the recovered modulated signal. Simulation results show that the proposed S-NOFDM can achieve better bit error rate performance in an additive white Gaussian noise channel and a little worse than OFDM in a Rayleigh channel, with less frequency resources required.

Multiple antennas can be used for increasing the amount of diversity or number of degrees of freedom in wireless communication systems. In this study, the authors consider a wireless half-duplex relay network consisting of one source–destination pair each with a single antenna and one relay with multiple antennas. They assume an approach where cooperation of the relay in the transmission depends on the decoding status at the relay. If the relay participates in transmission, the source and the relay use the distributed space-time code simultaneously. They derive the outage probability and the diversity-multiplexing tradeoff for the proposed protocol at high SNR. They have shown that the use of the centralised antennas with simultaneously decoding compared to the distributed antennas with independently decoding can improve the system performance.

In this study, the problem of two-dimensional (2D) direction of arrival estimation for uncorrelated signals with an L-shaped array is discussed. The estimated cross covariance matrix (CCM) between the sample data along the x-axis and the z-axis is constructed. The elevation angle of the signal is obtained by finding the sparse coefficients of the estimated CCM based on the discussion of statistical probability distribution of the sample data error. Once the elevation angle is obtained, with the non-coupling between the elevation angle and the azimuth angle, the azimuth angle of each source is estimated by the eigenvalue decomposition of the conjugate transpose matrix of the estimated CCM. The proposed algorithm has better estimation performance in the situation of low signal-to-noise-ratio cases but also the estimated azimuth and elevation angles are paired automatically. The performance of the proposed method is compared with some existing schemes and the effectiveness of the method is demonstrated by computer simulations.

In this study, the authors investigate the use of combined belief propagation (BP), mean field (MF) and expectation propagation (EP) message passing to achieve joint channel estimation and decoding (JCED) for orthogonal frequency division multiplexing where the channel sparsity is exploited, and a low-complexity BP–MF–EP-based JCED receiver is designed. Moreover, comparisons in message updating of state-of-the-art message passing-based JCED receivers are provided to illustrate the merits of the proposed one. In addition, message passing schedules are optimised to achieve better system performance. Simulation results verify the superiority of the proposed combined message passing receiver in terms of both bit-error-rate performance and convergence speed.

Distributed-compressed sensing (DCS)-based channel estimation of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing for relay communication is considered in this study. Specifically, the pilot allocation is addressed to optimise the channel estimation performance. All the existing works on DCS-based channel estimation pilot placement discussed on the mean square error (MSE) of the estimation probabilistically based on the mutual coherence. On the contrary, the authors try to address the MSE of the estimation directly and optimise the MSE directly and design a pilot pattern to optimise the performance of the estimation. By taking into account the optimisation approach, two combinatorial stochastic algorithms have been presented. These two algorithms utilise cross entropy approach in sequential and parallel form. Simulation results represent that the DCS-based MIMO relay channel estimation using optimised pilot placements will increase the performance from 3 to 12 dB as compared with the conventional least squares (LS) method. Furthermore, parallelism has demonstrated the performance gain. Moreover, the DCS-based MIMO relay channel estimation shows improvement in spectrum efficiency under the same bit error rate performance over the traditional LS-based channel estimation approach, respectively.

When small cells are densely deployed in the fifth-generation cellular networks, switching off a part of base stations (BSs) is a practical approach for saving energy consumption considering the variation of traffic load. The small-cell network with the massive multi-input–multi-output system is analysed in this study due to the dense deployment and low-power consumption. On the basis ofn the BS-switch-off strategy with distance constraints, the energy and coverage efficiency are investigated to illustrate the performance of the BS-switch-off strategy. Simulation results indicate that the energy efficiency and coverage efficiency of the proposed strategy are better than the random strategy. The energy efficiency increases with the BS intensity and the minimal distance, and a maximum coverage efficiency can be achieved with the increase of the BS intensity and the minimum distance. In this case, the optimal BS-switch-off strategy can be designed under this work in the actual scene.

In case where installation of optical fibre is not practically reliable, the new generation wireless communication popularised as free-space optics (FSO) systems can be used to transmit radio-frequency (RF) signals. FSO technology can efficiently transfer multiple RF signals, and this new technique is commonly referred as radio-on-FSO (RoFSO). The major challenges in this technology are atmospheric turbulence and pointing errors. In this study, the authors analysed the performance of RoFSO links employing the orthogonal frequency division multiplexing (OFDM) scheme under both modulation formats namely quadrature amplitude modulation and phase shift keying in the newly developed Málaga or M distribution turbulent channel model. The performance is evaluated with consideration of both scintillation and pointing errors in M distribution channel for higher values of the carrier-to-noise plus distortion ratio. M distribution channel serves as an effective generalised model which unifies all other available statistical channel models. The novel expressions of average bit-error rate has been derived and performance comparison has been done between the two modulation formats. This study identifies the crucial parameters that deteriorate the efficiency of the OFDM signal over FSO link which can be helpful in designing an optimal system.

In this study, an irregular low-density parity-check (iLDPC) coded rate compatible modulation (iLDPC-RCM) is proposed. A particularly designed interleaver is inserted between LDPC and RCM such that a fast convergence and a low bit-error rate (BER) can be achieved. The combination of strong error correction capability of irregular LDPC code and the seamless adaptation of RCM enables the proposed scheme to achieve a robust and spectrally efficient transmission over time-varying channels. In addition, a joint belief propagation algorithm is proposed to lower the BER of iLDPC-RCM and speed up the convergence of iterative decoding. Simulation results show that the proposed iLDPC-RCM improves the BER and throughput performance while maintaining an acceptable computational complexity at the same time, validating its advantages over the regular LDPC coded RCM with the same coding rate.

For a non-linear sucker-rod pumping system, a surface dynamometer card estimation algorithm based on a particle filter is presented. The dynamometer card is a plot of the polished rod load at various positions of a pump stroke. Since the polished rod load measured by a load sensor is frequently affected by drift problems, a local characteristic correlation method is proposed while building the state-space model for the pumping unit. The local characteristic correlation method makes the system insensitive to load drift problems. Moreover, the prior data recorded from different wells are used to construct the importance density. To make the k-time importance density closer to the real posterior distribution, current measurement information is used. The performance of the proposed algorithm is evaluated on the actual operating data of a Xinjiang oil field containing typical daily production activities that can cause sudden system state changes. The results show that the proposed algorithm can adapt to sudden changes of the underground environment caused by various human factors, and it can provide robust estimation for multi-well long-term state tracking.