In this chapter, we first review the state-of-the-art schemes for nonorthogonal multiple access where multiple users share the satellite channel radio resources. Among different grant-based and grant-free access schemes, we focus on nonslotted techniques, we study some decoding strategies to improve the performance of asynchronous contention resolution diversity ALOHA. Our preliminary results show that the performance of the decoder can be improved significantly if the information on overlapping bursts' powers and the exact differential delay among the incoming bursts are known at the receiver. We present the simulation results for a simple model and discuss the possible generalizations to a more realistic system scenario. Finally, we shortly discuss the efficiency of the physical layer abstraction methods under our model assumptions.

To achieve reliable and green communication in the internet of things (IoT) networks, the authors extend the traditional half-duplex quantise-and-forward (QF) cooperation into the simultaneous wireless information and power transfer (SWIPT) regime. This study investigates the achievable rate of the SWIPT-based half-duplex QF cooperation with the channel state information available only at the receivers. The source and destination are provided by the external power supply and the relay simultaneously implements the information transmission and the energy harvesting by SWIPT technology with the power-splitting protocol. The achievable rate of the proposed system over the additive white Gaussian noise channels is analysed and further maximised by optimising the power-splitting factor. Furthermore, the expected rate of the proposed system over the slow-fading channels is analysed. Theoretical analysis and simulation results show that the achievable rate or expected rate of the SWIPT-based QF cooperation is obviously superior to that of the SWIPT-based amplify-and-forward or SWIPT-based decode-and-forward cooperation. Meanwhile, the SWIPT-based QF cooperation can achieve similar performance to the traditional QF cooperation when the external power supply at the relay is not provided.

The vehicular ad hoc network (VANET) is a promising technology to improve the comfort and safety of passengers, roads and urban traffic. Applications applied to VANETs require efficient routing protocols. Urban environments include tunnels, subways, overpasses, and multilevel highways, which indicate the multilevel information environment and specific conditions of radio channel dissemination. In this paper proposed a three-dimensional (3D) evidence theory based, opportunistic routing protocol, called 3DEOR, which address the above issues using a new hybrid criterion called PAL. The PAL criterion includes three metrics of packet delivery probability to compensate for unreliable dissemination environments, packet advancement appropriated to 3D environments to reduce the number of hop counts and level to improve link connectivity. Prioritise the relay set members based on the new criteria to select the best relay node. In cases where there is no certainty, the evidence theory can be a good choice for combining the three metrics of the PAL criterion. The simulation results show the superiority of the proposed protocol over the 3D link state aware geographic opportunistic (3DLSGO) and 3D greedy perimeter stateless routing (3DGPSR) protocols in network performance indices such as packet delivery rate, end-to-end delay and average hop count.

Research on underwater acoustic sensor networks has become a compelling field in recent years since resources on land are being depleted. Therefore, robust and efficient routing protocols are needed to ensure the reliability of message gathering and transmitting in underwater sensor networks. In the process of biological foraging in nature, creatures such as insects can find paths while adapting to dynamic environmental conditions through group cooperation, which provides a new perspective for research on routing protocols. In this study, the authors proposed an ant colony algorithm-based routing protocol (ACAR). In ACAR, the pheromone with a novel physical meaning and concentration changing mechanism is utilised to guide ants (path establishing packets) to the sink node. In addition, node depth information is used to decrease redundancy in the underwater environment. The routing process can be summarised in three parts: pheromone list setup, routing decision and damaged path repair. Simulation results, carried out on an underwater simulator based on NS-2, showed that ACAR outperforms other schemes with regards to network lifetime with a relatively better delivery ratio and latency in the proposed network scenarios.

Ever since the idea of buffers was incorporated in wireless communications, buffer-aided relaying has become an emerging breakthrough in the world of transmitting and receiving signals. Equipping the relays with buffers adds a new degree of freedom capable of enhancing numerous quality-of-service (QoS) metrics including throughput, outage probability, power efficiency and physical-layer security. The QoS enhancement is achieved by compromising the end-to-end delay that is inflicted by storing the packets in the relays' buffers until a suitable source–relay or relay–destination link is selected. In this context, the selection of a relay for transmission/reception is important since it governs the QoS-delay trade-off that can be contemplated. In this survey, the authors review and analyse various link selection protocols in buffer-aided relaying systems. These relaying strategies are categorised and contrasted according to their performance levels, limitations, applications, system model assumptions and complexity. Finally, they discuss current challenges, and highlight future research directions.

In this paper, the problem of interference management is investigated in the downlink of multi-user multiple-input multiple-output two-hop interference channel under various scenarios of channel state information (CSI) and antenna correlation. Interference alignment (IA) in the space dimension is a powerful tool to solve this problem. Iterative IA algorithms are adopted in both the first and the second hops transmissions independently. After aligning interfering signals, the recovery of the transmitted signal vector is performed based on zero-forcing and semi-definite relaxation detectors. Furthermore, the impacts of the imperfect CSI and antenna correlation on sum-rate are investigated for decode-and-forward (DF) and amplify-and-forward relaying protocols. When the system is proper but IA is not completely feasible, the performance of minimum interference leakage (MIL) is compared with rank-constrained rank minimisation (RCRM) algorithm in DF protocol. RCRM algorithm is more sensitive to CSI such that the channel uncertainty easily leads to an increase in the interference matrix rank. According to the simulation results, for the case of perfect CSI, RCRM makes further interference-free dimensions which leads to better performance than MIL, but for the case of imperfect CSI, close performance is observed.

IEEE 802.15.4 has been widely accepted as the de facto standard for wireless sensor networks (WSNs). However, as in their current solutions for medium access control (MAC) sub-layer protocols, channel efficiency has a margin for improvement, in this study, the authors evaluate the IEEE 802.15.4 MAC sub-layer performance by proposing to use the request-/clear-to-send (RTS/CTS) combined with frame concatenation and block acknowledgement (BACK) mechanism to optimise the channel use. The proposed solutions are studied in a distributed scenario with single-destination and single-rate frame aggregation. The throughput and delay performance is mathematically derived under channel environments without/with transmission errors for both the chirp spread spectrum and direct sequence spread spectrum physical layers for the 2.4 GHz Industrial, Scientific and Medical band. Simulation results successfully verify the authors’ proposed analytical model. For more than seven TX (aggregated frames) all the MAC sub-layer protocols employing RTS/CTS with frame concatenation (including sensor BACK MAC) allow for optimising channel use in WSNs, corresponding to 18–74% improvement in the maximum average throughput and minimum average delay, together with 3.3–14.1% decrease in energy consumption.

Designing a scalable and efficient application layer protocols for the Internet of Things (IoT) environment is an ongoing problem. The constrained application protocol (CoAP) offering RESTful services for IoT devices implements a simple congestion control mechanism. This study proposes and analyses the distance-based congestion control CoAP (DCC-CoAP) for the current state of the network and accordingly calculate the future flow rate to handle congestion. The authors’ main idea is to use the combination of distance between nodes and round trip time (RTT) measurements which limits the losses of CoAP messages, which is an efficient way to predict the network congestion. The user-defined options, i.e. retransmission counter and timestamp of sent and received CON and ACK messages are introduced for mapping CON to ACK and measure RTT. The comparative analysis of the DCC-CoAP with other congestion control mechanism like default CoAP, CoCoA+ is also highlighted in this study. With low additional computations, future RTT can be measured for avoiding congestion, and retransmission timeout varies with distance to avoid transaction losses. An algorithm with varying data rate has been used in homogeneous and mixed traffic to calculate the parameters in terms of packet delivery ratios, delay and retransmission count.

Channel selection is a challenging task in cognitive radio vehicular networks. Vehicles have to sense the channels periodically. Due to this, a lot of time is wasted which could have been utilised for transmission of data. Employing road side units (RSUs) in sensing can prove to be useful for this purpose. The RSUs may select the channel and allocate it to the vehicles on demand. However, this sensing should be proactive. RSUs should know in advance the channel to be allocated when requested. For this purpose, a deep reinforcement learning algorithm namely deep reinforcement learning based optimal channel selection is proposed in this study for training the network according to the previously sensed data. Proposed protocol is simulated and results are compared with the existing methods. The packet delivery ratio is increased by 2%, throughput is increased by 1.8%, average delay is decreased by 2% and primary user collision ratio is reduced by 3.2% when compared with similar recent work by varying number of vehicles. On the other hand, when compared with similar recent work by varying channel availability, the packet delivery ratio is increased by 4.5 %, throughput by 4.3%, average delay is decreased by 3% and PU collision ratio by 5.5%.

Despite the importance of cyber-security for networked control systems, no suitable cryptosystem exists for networked control systems that guarantees stability and has low computational complexity. This study proposes a novel dynamic ElGamal cryptosystem for encrypted control systems. The proposed cryptosystem is a multiplicative homomorphic cryptosystem, and it updates key pairs and ciphertexts by simple updating rules with modulo operations at every sampling period. Furthermore, the authors modify the proposed cryptosystem by using a dynamic encoder and decoder so that the asymptotic stability of the encrypted control systems is guaranteed. Numerical simulations demonstrate that the encrypted controller with the proposed cryptosystem achieves asymptotic stability while randomly updating key pairs and ciphertexts. The feasibility of the proposed encrypted control system is evaluated through regulation control with a positioning table testbed. The processing time of the proposed encrypted control system is on the order of milliseconds, indicating that the system achieves real-time control.