Due to the explosion of mobile users and the ever-increasing heterogeneity and scale of wireless networks, traditional communication protocols and optimizing methods can not satisfy future wireless network (FWN) requirements. As promising technologies, artificial intelligence (AI) and blockchain are deemed as the solution for the FWN. AI, famous for its big data processing ability, will enable the FWN to self-update itself to better adapt to the dynamic network condition. Blockchain, as a distributed ledger, can guarantee data integrity, security, and privacy. In this survey, we overview the concept of AI and blockchain and present their state-of-the-art applications in wireless networks. The potential of AI and blockchain is still huge and waiting to be fully explored in wireless networks. Therefore, we introduce how AI and blockchain can assist each other in FWNs. Furthermore, we explore the current constraints of applying both technologies in the FWNs. In the final part, we discuss the future direction of the deployment of AI and blockchain in FWNs.

Practical Byzantine Fault Tolerance (PBFT) is one of the most popular consensus mechanisms for the consortium and private blockchain technology. It has been recognized as a candidate consensus mechanism for the Internet of Things networks as it offers lower resource requirements and high performance when compared with other consensus mechanisms such as proof of work. In this paper, by considering the blockchain nodes are wirelessly connected, we model the network nodes distribution and transaction arrival rate as Poisson point process and we develop a framework for evaluating the performance of the wireless PBFT network. The framework utilizes slotted ALOHA as its multiple access technique. We derive the end-to-end success probability of the wireless PBFT network which serves as the basis for obtaining other key performance indicators namely, the optimal transmission interval, the transaction throughput and delay, and the viable area. The viable area represents the minimum PBFT coverage area that guarantees the liveness, safety, and resilience of the PBFT protocol while satisfying a predefined end-to-end success probability. Results show that the transmission interval required to make the wireless PBFT network viable can be reduced if either the end-to-end success probability requirement or the number of faulty nodes is lowered.

The ever-increasing mobile users pose a great challenge to the current centralized structure, where the failure of the network center significantly compromises privacy and data security. Practical byzantine fault tolerant (PBFT), a voting-based consensus blockchain, is a plausible solution to the wireless network for its distributed and decentralized traits, and it is not computation-intensive. The view change mechanism guarantees the liveness and resilience of PBFT, but it also causes delay. Moreover, spectrum is usually shared in the wireless network, introducing additional channel contention. Hence, we develop a framework investigating the impacts of channel contention on the wireless PBFT network using the IEEE 802.11 protocol. Based on the Markov model, we derive the throughput, transmission success probability, and transaction confirmation delay of such a network. Furthermore, we derive the view change delay in reference to the transaction confirmation delay. The analysis and results show that channel contention impacts in two ways. It impairs the success probability and increases the chance of view change. Optimal pairs of packet arrival rate and contention window size are formulated to maximize the consensus's success probability without sacrificing the overall network performance. Further, the optimal pairs under different network sizes are demonstrated for straightforward guidance.

Blockchain has shown significant potential as a key enabler in privacy and security in the forthcoming 6G wireless network, due to its distributed and decentralized characteristics. Practical byzantine fault tolerance (PBFT) emerges as a prominent technology for deployment in wireless networks due to its attributes of low latency, high throughput, and minimal computational requirements. However, the high complexity of communication is the bottleneck of PBFT for achieving high scalability. To tackle this problem, this paper proposes a novel framework of PBFT, where the inter-node communication during the normal case operation is completed through base stations. The uplink and downlink communication between the base station and nodes are modelled based on the signal-to-interference-plus-noise ratio (SINR) threshold. A novel ‘timeout’ mechanism is incorporated to reduce the communication complexity. The performance is evaluated by metrics including consensus success probability, communication complexity, view change delay, view change occurrence probability, consensus delay, consensus throughput and energy consumption. The numerical results show that the proposed scheme achieves higher consensus success probability and throughput, lower communication complexity and consensus delay compared to the conventional PBFT. The results of view change delay and view change occurrence probability and the optimal configuration provide analytical guidance for the deployment of wireless PBFT networks.