In this chapter, we present a new hardware test-bed to demonstrate closed-loop precoded communications for interference mitigation in multibeam ultrahigh throughput satellite systems under realistic payload and channel impairments. We build the test-bed to demonstrate a real-time channel aided precoded transmission under realistic conditions such as the power constraints and satellite-payload nonlinearities. We develop a scalable architecture of an SDR platform with the DVB-S2X piloting. The SDR platform consists of two parts: analog-to-digital (ADC) and digital-to-analog (DAC) converters preceded by radio frequency (RF) front end and field-programmable gate array (FPGA) backend. The former introduces realistic impairments in the transmission chain such as carrier frequency and phase misalignments, quantization noise of multichannel ADC and DAC, and nonlinearities of RF components. It allows evaluating the performance of the precoded transmission in a more realistic environment rather than using only numerical simulations. We benchmark the performance of the communication standard in realistic channel scenarios, evaluate received signal SNR, and measure the actual channel throughput using LDPC codes.

The increasing demand of highly efficient wireless communication systems that supports high data-rates has been manifest with the fifth-generation (5G) system of systems. Satellite communications systems are to play significant role in supporting this system in terms of significant capacity enhancement, in addition to its ability to serve area where the terrestrial infrastructure is unable to provide services. The DVB-S2 standards are the candidates that will support this quest. The extension of the second generation of the DVB-S2X has further justified this advantage by incorporating higher modulation and coding schemes (MODCODs) such as the 64-APSK, 128-APSK, and 256-APSK. However, with the increasing utilization of on-the-move applications and services, the classical limitations of the satellite links in a mobile environment pose a problem to the seamless realization of capacity. These problems include signal fading due to path blockage, multipath propagation, and shadowing. A realistic mobile satellite channel has been modeled in MATLAB^® using realistic terrain data which is processed in Systems Tool Kits simulator (STK) in order to determine the satellite-receiver access time leading to the determination of the Markovian Transition Matrix used for channel state condition. The performance of a good selection of DVB-S2X MODCODs has been presented and the new mobile channel has been used to test the effect on mobility on system performance. The result indicated that the mobility of the earth station causes degradation to the link performance, with scenarios of higher values of Rician K-factor, denoting the dominance of line-of-sight (LOS) being the best. Therefore, the need for further highly efficient receiver processing and optimal thresholds switching techniques that can support mobile channels in terms of high data-rate and availability is more than a prerequisite for the satellite component of the 5G systems.

In this chapter, we investigate a DVB-RCS2-based satellite communication system consisting of a gateway, a satellite, and a return channel satellite terminal (RCST). We formulate an optimization problem to maximize the transmission rate of the system. To solve the problem, we propose an adaptive coding and modulation (ACM) and power control scheme for return link transmission based on the return channel condition and power headroom of the RCST. Simulation results show that the proposed ACM and power control scheme increases the transmission rate as the transmit power of RCST and satellite increases or the power headroom of RCST increases.

This chapter revisits the impact of channel phase in multibeam multicast satellite precoding. First, we analyze the unicast case showing that the phase components relative to the different slant paths to each user do not affect the precoding performance. Then, we indicate that for the multicast transmission, the mentioned phase effect may have impact depending on the employed clustering technique. Finally, we propose an alternative clustering solution based on normalizing out the phase components relative to the different slant paths. According to our simulation results, this novel clustering technique provides robustness to these phase components and also behaves better than previously reported clustering schemes.

Non-reciprocity limits the potential of time division duplexing (TDD) massive multiple-input and multiple-output (MIMO) systems. Due to the reciprocal channel, there is no need for downlink (DL) pilot transmission implies computational complexity reduction and saving precious time resources. In this study, the DL channel matrix is estimated using the uplink channel matrix by a novel reciprocity calibration technique. Non-reciprocity arises due to the hardware mismatch (HM) across the base station (BS) and the user terminal (UT)/both. Its detrimental effect causes amplitude and phase impairment in the downlink signal transmission. Since a massive MIMO network has a large number of antenna elements across the BS, hence the instantaneous HM coefficient cannot be determined accurately. For solving such a problem, the authors use the statistical response of the hardware unit. Considering a complex Gaussian hardware response across each antenna terminal, the probability density function (PDF) of amplitude and phase mismatch is derived. They also derive the joint PDF of amplitude and phase mismatch, considering the HM. Simulation results address the sensitivity and complexity for evaluating the sum-rate capacity under three linear precoders (matched filter, regularized zero-forcing, and zero-forcing), which validate their effectiveness in this scenario.

This work proposes a machine learning detection scheme for wireless orbital angular momentum (OAM) communication systems. The new scheme works for single-input–single-output (SISO) and multiple-input–single-output (MISO) wireless communication between the transmitter and the receiver. The transmitter encodes its data in OAM modes which are constructed using Laguerre–Gaussian beam form. The transmitted beams travel through a wireless channel with weak to medium turbulence strength and they arrive at random positions on the same receiver area. The authors proposed detection scheme allows the reception of multiple overlapping beams without prior knowledge of beams centre positions. The proposed scheme uses a novel technique of receiver segmentation and space filtering along with neural network to decode the received beams. Simulations show the detection efficiency and the enhanced performance of their proposed scheme for the SISO case and the MISO case with 2, 4, and 16 beams.

MIMO systems employing sphere decoding (SD) algorithm are known to achieve near maximum likelihood (ML) performance at a reduced complexity by restricting the candidate search space to a sphere of a certain radius. The performance of SD depends on the precise estimation of its soft output. In this paper, a low complexity modified Likelihood Ascent Search (LAS) algorithm is proposed to be used within a SD receiver in order to precisely estimate the counter-hypothesis for its winner candidates. The LAS algorithm is modified to search for the best counter-hypothesis in only one-half of the signal lattice thereby improving the performance of MIMO receiver. Our results challenge the popular perception that for a SD receiver a large number of candidates within the search sphere is essential for good performance. Instead, it is shown that accurate estimation of the counter-hypothesis is equally important and in fact, the performance of the proposed augmented SD receiver with only single candidate approaches that of a classical SD with multiple candidates. Bit error rate performance of the proposed method when compared with the existing research works on soft output generation for the same number of candidates shows that our proposed method outperforms them by upto 3 dB.

In this study, secure communications in a two-way relaying wiretap system with a silent eavesdropper are studied. Under the assumption that the channel state information relating to the eavesdropper is unknown at legitimate nodes, the precoding vectors at the two source nodes are jointly designed to decrease the wiretap capacity at the eavesdropper. The derived relationship between the two precoding vectors is partially similar in nature to the linear minimum mean squared error (MMSE) equaliser. An iterative process is proposed to jointly achieve two precoding vectors, and its convergence is proved. Simulation results are presented to demonstrate that the proposed MMSE-based precoding algorithm can be used for source nodes with any number of antennas, and outperforms its conventional zero-forcing- and matched-filter-based counterparts. Signal leakage from the relay node to the eavesdropper is nearly completely suppressed by the proposed precoding design.

This study presents an analysis for evaluating the physical layer (PHY) security performance of a two-hop amplify-and-forward cooperative relaying system employing Alamouti orthogonal space–time block coding (OSTBC) in the presence of an eavesdropper, where the transmit antennas for OSTBC are assumed to be spatially correlated. It is also assumed that the authorised main channels as well as the non-authorised eavesdropper channels follow Rayleigh fading distribution. Closed-form mathematical expressions are derived for three performance metrics for evaluating the PHY security, namely the probability of non-zero secrecy capacity, the secrecy outage probability, and the average secrecy capacity. Using the extensive numerical results obtained from the derived mathematical expressions, the impact of antennas correlation on the PHY secrecy performance of the system is studied and evaluated under different parameters. It is also shown that the antennas correlation corresponding to the main channels has more impact than the antennas correlation corresponding to the eavesdropper channels.

Optimising the coding bit-rates and activity rates of sensor nodes is essential for the functionality and survival of wireless sensor networks as these rates not only affect the amount of information collected by the network, but also affect its power consumption. This study proposes a framework for joint coding bit-rates and activity rates optimisation (CARO) of sensor nodes in wireless visual sensor networks under limited energy constraints. The framework uses the concept of accumulative visual information (AVI) as a measure of the amount of visual information collected from a sensor node. The authors propose two optimisation algorithms for the following two cases: (I) networks with predetermined operation time, where algorithm CARO I maximises the AVI of the network over its predetermined operation time. (II) Best effort networks, where algorithm CARO II maximises the network operation time under constraints on the collected visual information. Simulations show that optimising the rates using CARO maximises the AVI of the network and extends its operation time compared to the straightforward solution when all nodes have equal activity rates. This is because the authors' framework takes into consideration that different nodes in different locations may operate under different conditions and collect information of different significance.