Blockchain Papers

Jamal Hussain Arman, Fazal Muhammad, Muhammad Abdullah, Adil Zulfiqar

No abstract is available for this record.

Piotr Stolarski, Szczepan Górtowski, Elżbieta Lewańska

No abstract is available for this record.

Yuhang Yao, Syed A. Jafar

An open question recently posed by Fawzi and Ferme [IEEE Transactions on Information Theory 2024], asks whether non-signaling (NS) assistance can increase the capacity of a broadcast channel (BC). We answer this question in the affirmative, by showing that for a certainK-receiver BC model, called Coordinated Multipoint broadcast (CoMP BC) that arises naturally in wireless networks, NS-assistance provides multiplicative gains in both capacity and degrees of freedom (DoF), even achievingK-fold improvements in extremal cases. Somewhat surprisingly, this is shown to be true even for 2-receiver broadcast channels that are semi-deterministic and/or degraded. In a CoMP BC,Bsingle-antenna transmitters, supported by a backhaul that allows them to share data, act as oneB-antenna transmitter, to send independent messages toKreceivers, each equipped with a single receive antenna. A fixed and globally known connectivity matrix specifies for each transmit antenna, the subset of receivers that are connected to (have a non-zero channel coefficient to) that antenna. Besides the connectivity, there is no channel state information at the transmitter. The receivers have perfect channel knowledge. We show that NS-assistance has no DoF advantage in a fully connected CoMP BC. The DoF region is fully characterized for a class of connectivity patterns associated with tree graphs, for which the classical sum-DoF value is shown to be the number of leaf nodes, while the NS-assisted sum-DoF value is the total number of all (non-root) nodes. For arbitrary connectivity patterns, the sum-capacity with NS-assistance is bounded above and below by the min-rank and triangle number of the connectivity matrix, respectively, leading to matching bounds in many cases, e.g., if min(B,K) ≤ 6. While translations to Gaussian settings are demonstrated, for simplicity most of our results are presented under noise-free, finite-field (Fq) models. Converse proofs for classical DoF are found by adapting the Aligned Images bounds to the finite field model. Converse bounds for NS-assisted DoF/capacity extend the same-marginals property to the BC with NS-assistance available to all parties. Beyond the BC setting, even stronger (unbounded) gains in capacity due to NS-assistance are established for certain ‘communication with side-information’ settings, such as the fading dirty paper channel.

Jorge Soria, Jorge Moya Velasco, Carlos Estévez-Mendoza

Decentralized Physical Infrastructure Networks (DePIN) represent an emerging organizational form for operating physical infrastructure through blockchain-based coordination. DePIN through decentralized protocols and token-based payment mechanisms incentivize independent agents to deploy, maintain, and monetize real-world infrastructure, such as wireless networks, storage units, or sensors. This article presents a first formal economic analysis of DePIN architectures, modelling investment decisions under network effects in a blockchain-native Decentralized Autonomous Organization (DAO), with protocol-defined reward schemes. It establishes the equilibrium conditions that support decentralized provision, where token prices internalize participation, service reliability, and network coverage. Furthermore, it identifies a minimum viable coverage threshold determined by costs and network effects. Through a multi-agent machine learning simulation, we confirm that decentralized provision improves efficiency compared to centralized models. The results support the economic viability of DePIN and provide design guidelines for future decentralized infrastructure protocols. Finally, we propose an DAO incentive mechanism to implement First Best provision in Decentralized Physical Infrastructure Networks.

Zhen Gao, Shipeng Lin, Zezhong Li, Jiuzhi Zhang · 8 authors

The symbiotic radio network (SRN) plays a crucial role in green communication solutions by facilitating cooperative communication between devices of primary and secondary links, leading to enhanced transmission quality and optimized resource efficiency. For the joint demodulation of primary and secondary signals, the multiparty trust is essential for operators with different interests. Building multiparty trust in a decentralized manner is challenging for the implementation of the SRN. As an emerging distributed ledger technology, blockchain provides multiparty trust between unreliable devices to share data and resources cooperatively. This paper proposes a consortium Blockchain-based Cooperative Communication scheme for SRN (BCC-SRN), where Hyperledger Fabric is used as the trust anchor with better security, higher throughput, and more flexible organization. In particular, a credit-based incentive mechanism is established to encourage different parties to behave according to the negotiated contracts. The credit is recorded by smart contracts and adjusted based on the contribution of the corresponding cooperators. Simulation results prove that the proposed BCC-SRN is highly effective in improving cooperation security and transmission quality.

Elham Hashemi Nezhad, Antonio Di Maio, Torsten Braun

The orchestrators’ deployment problem presents numerous challenges in 6G Network Radio Access Networks due to their large-scale, dynamic conditions, and variable user demands. Most works propose single- or hierarchical-orchestrator solutions, which offer poor resiliency, high signaling overhead, and slow adaptation to variable network dynamics. To tackle these challenges, we propose an online, data-driven, fully decentralized, Multi-Agent Reinforcement Learning (MARL)-based, self-organization orchestrator deployment system for 6G networks, which jointly optimizes the tradeoff between user throughput and fairness, based on time-varying system conditions. In the proposed approach, a flexible variable number of decentralized, cooperative, peer self-organization agents autonomously adapt their associated orchestrator’s deployment location and activity to optimize network operation, without requiring centralized coordination. Simulations show improvements of up to 77% in user throughput compared to Hierarchical and Single Orchestrator baselines in a broad range of realistic scenarios.

Haixia Cui, Bo Xie, Hongjiang Wang, Victor C. M. Leung

Wireless channel modeling is critical to understanding and optimizing signal transmission. Wireless channels are influenced by many factors, including path loss, reflection, fading, and interference, making them complex and difficult to model and predict. Although some traditional wireless channel modeling methods are effective, they have limitations in handling complex multipath effects and nonlinear characteristics. Generative artificial intelligence (GAI) has the ability to generate robust data and therefore can be potentially used to model realistic wireless channel characteristics. However, there exist some challenges in GAI for wireless channel modeling, including physical layer network security issues, limited generalization ability, and the bandwidth consumption of centralized training. This article introduces a GAI-based wireless channel modeling framework, which leverages blockchain and federated learning to address efficiency, network security, and data privacy concerns in GAI channel modeling. Blockchain technology, through distributed ledgers and smart contracts, enables resource sharing and efficient utilization, enhancing computational efficiency and reducing network security risks. Federated learning allocates training tasks to different devices and nodes, thus allowing model training without centralizing data, protecting user privacy, and reducing network bandwidth usage. This article demonstrates the performance and effectiveness of the proposed framework through numerical results.

Inam Ullah, Ali Arishi, Sushil Kumar Singh, Faisal Alharbi · 8 authors

The rapid advancement of 6G communication networks presents both considerable problems and opportunities in network management, necessitating sophisticated solutions that extend beyond conventional methods. This study seeks to investigate and evaluate autonomous network management solutions designed for 6G communication networks, highlighting their technical advantages and potential implications. We examine the role of Artificial Intelligence (AI), Machine Learning (ML), and network automation in facilitating self-organization, optimization, and decision-making within critical network domains, including spectrum management, traffic load balancing, fault detection, and security and privacy. We examine the integration of edge computing and Distributed Ledger Technologies (DLT), specifically blockchain, to improve trust, transparency, and security in autonomous networks. This study provides a comprehensive understanding of the technological developments driving fully autonomous, efficient, and resilient 6G network infrastructures by methodically analyzing existing methodologies, identifying significant research gaps, and exploring potential prospects. The results offer significant insights for researchers, engineers, and industry experts involved in the development and deployment of advanced autonomous network management systems.

Mamoon M. Saeed, Rashid A. Saeed, Mohammad Kamrul Hasan, Elmustafa Sayed Ali · 8 authors

After adopting 5G technology, businesses and academia have started working on sixth-generation wireless networking (6G) technologies. Mobile communications options are expected to expand in areas where previous generations could not do so. 6G networks are anticipated to be constructed using various diverse technologies. These encompass diverse cutting-edge advancements, such as distributed ledger systems like blockchain, visible light communications (VLC), post-quantum cryptography, edge computing, molecular communication, THz, and other advances. These advances necessitate a reassessment of previous security strategies from a security perspective. In the future, networks must adhere to stricter criteria for authentication, encryption, access control, connectivity, and detection of harmful activities. Ensuring privacy and dependability necessitates the implementation of supplementary security protocols. The essay explores the primary concerns and challenges related to the security of the 6G network. This paper describes the improvements in security in communications from 1G through 6G. This paper divides security in the sixth generation into three layers: physical, connection, and service. Each layer-by-layer discusses the standard technologies and security issues for each technology proposed in each sixth-generation security layer. All proposed solutions for each of the three layers are discussed in Sixth Generation Security. It also reviews all proposed solutions for each layer, indicating the proposed solution and its limitations.

Kranthi Kumar Singamaneni, Anil Kumar Budati, Raenu Kolandaisamy, Vijaya Saradhi Dommeti · 5 authors

The advent of 6G networks places very high demands on ultra-low latency, high throughput, and quantum-secure communication to power Industry 5.0 use cases. Traditional blockchain architectures, given their decentralized and secure nature, often fall short in meeting the performance and security requirements of such an ecosystem. In this paper, we present a post-quantum blockchain architecture that employs CRYSTALS-Dilithium and SPHINCS+ for digital signatures and block and transaction verification, respectively, along with zk-STARKs to facilitate scalable zero-knowledge proof-based privacy, and a DPoS+VDFs consensus protocol to satisfy fairness and efficiency. We prototyped and evaluated the proposed framework with a benchmarking setup composed of Python, PQClean, liboqs, and Google Benchmark tools. Experimental results demonstrate that the system achieves a 40% reduction in latency, a 35% increase in transaction throughput, and a 25% reduction in computational overhead due to the integration of zk-STARK. Furthermore, finality time for consensus was reduced by 30% by using the hybrid DPoS-VDF consensus approach. Comparative studies with various lattice-, hash-, and code-based quantum cryptographic primitives have shown that CRYSTALS-Dilithium and SPHINCS+ outperform others in key generation, signing, and verification performance indicators, and thus qualify as optimal solutions for edge-centric 6G infrastructures. Conversely, zk-Starks showed near-optimal timeliness and verification effectiveness among the several examined zero-knowledge proof schemes. These findings validate the proposed framework as an efficient, scalable, and performance-enhanced blockchain solution for securing industrial ecosystems with latency sensitivity in a 6G-enabled environment.

D. Balakumar, S. Nandakumar

One of the greatest ways to guarantee that networks designed for fifth generation (5G) and beyond reach the required levels of spectrum efficiency (SE) is through nonorthogonal multiple access (NOMA). This work presents two new blockchain-based techniques that take advantage of massive multiple input multiple output in a single-cell network to improve performance. NOMA power domain is used in the 5G cooperative cognitive radio network (CCRN) to improve the SE of the downlink. This study investigates a novel cooperative NOMA-based CCRN for underlay spectrum sharing. A cooperative NOMA technique is proposed by considering the access modes of relays and secondary users (SUs) on the secondary network. The proposed system's performance is assessed with respect to random channel characteristics, frequency-selective Rayleigh fading and perfect successive interference cancellation (SIC). The first signal decoded by SU identifies the relay states with the best channel quality between users and the destination users to offset the bit error rate. The throughput dropped during the period because of the perfect SIC. The precise closed-form expressions for the system throughput of the secondary network are derived under the interference constraint of the primary network to evaluate the efficacy of the suggested cooperative strategy. The suggested approaches are assessed under various conditions using the MATLAB application by considering varying transmit power levels, power location coefficients and lengths. In every case, four users are assumed to be using a 90 MHz bandwidth and M-ary Quadrature Amplitude Modulation technology. • Each user (PU and SU) is transformed into blockchain-like blocks that collaborate to create a decentralised network. • The cooperative users' authentication verifies the energy detection technique for spectrum sensing and its results. • Blockchain technology is used to leverage the security of the massive-MIMO network and improve user performance by using digital signatures to confirm PU and MU's identities and preventing MU from using PUs bandwidth. • The identification of an in individual sensing for broadcast channel, cooperative channel for M-MIMO DL PD NOMA with relay CCRN is use to validate the energy detection, throughput, spectrum efficiency, and BER.

Sadaf Bukhari, Kashif Sharif, Liehuang Zhu, Chang Xu · 6 authors

The advent of 6G networks promises revolutionary advances in dynamism, intelligence, and decentralization. Realizing the full potential of 6G requires adaptable service level agreements (SLAs) that can optimize performance based on dynamic network conditions. In this paper, we suggested a method based on the Hyperledger Sawtooth blockchain’s smart contract with the Reptile meta-learning algorithm to solve the rigidity of static SLA and centralization problems. In order to sustain the quality of service in the radio access network and core network domain of 6G networks, this work focuses on SLA management for efficient resource allocation for the eMBB-plus slice. Our approach entails breaking down static SLAs into finer-grained components, transferring those components onto Hyperledger Sawtooth smart contracts, and using the Reptile meta-learning algorithm to forecast SLA metrics and resource requirements. A dynamic tariff model, also proposed within the smart contract, handles increased user demands. We evaluate the solution by analyzing Reptile performance, resource allocation, and SLA violations under dynamic demands. Results demonstrate the efficiency of this AI-driven, blockchain-based approach for automated, optimized 6G eMBB-plus resource management adhering to dynamic fine-grained SLAs. This work highlights the synergistic potential of AI and blockchain for trusted and intelligent 6G service delivery.

Haoxiang Luo, Gang Sun, Cheng Chi, Hongfang Yu · 5 authors

Symbiotic communication (SC) is known as a new wireless communication paradigm, similar to the natural ecosystem population, and can enable multiple communication systems to cooperate and mutualize through service exchange and resource sharing. As a result, SC is seen as an important potential technology for future sixth-generation (6G) communications, solving the problem of lack of spectrum resources and energy inefficiency. Symbiotic relationships among communication systems can complement radio resources in 6G. However, the absence of established trust relationships among diverse communication systems presents a formidable hurdle in ensuring efficient and trusted resource and service exchange within SC frameworks. To better realize trusted SC services in 6G, in this paper, we propose a solution that converges SC and blockchain, called a symbiotic blockchain network (SBN). Specifically, we first use cognitive backscatter communication to transform blockchain consensus, that is, the symbiotic blockchain consensus (SBC), so that it can be better suited for the wireless network. Then, for SBC, we propose a highly energy-efficient sharding scheme to meet the extremely low power consumption requirements in 6G. Finally, such a blockchain scheme guarantees trusted transactions of communication services in SC. Through ablation experiments, our proposed SBN demonstrates significant efficacy in mitigating energy consumption and reducing processing latency in adversarial networks, which is expected to achieve a sustainable and trusted 6G wireless network.

Muhammad Rizwan, Mudassir Ali, Ammar Hawbani, Xingfu Wang · 8 authors

Vehicle-to-grid (V2G) energy trading based on distributed ledger technologies (DLT), such as blockchains, has attracted much attention due to its promising features, including ease of deployment, decentralization, transparency, and security. However, existing DLT-based models do not support microtransactions due to the low value of such transactions relative to the incentives offered to transaction verifiers. To address this issue, we propose an IOTA DLT-based efficient and secure energy trading model for V2G networks, where electric vehicles (EVs) and grids negotiate energy prices in an off-chain manner. The proposed model utilizes a privacy-preserving protocol to prevent real-time tracking of EV locations. We develop a Stackelberg game model to represent the interactions between the EVs and grids, from which we derive a pricing scheme and propose a deposit mechanism to prevent fake energy trading between the EVs and grids. Extensive simulations demonstrate that our proposed scheme outperforms existing V2G energy trading mechanisms regarding transaction efficiency, provides enhanced EV privacy, and improves resilience against fake energy trading. Offering robust computational performance and addressing computational complexity (time, space, and message), our model presents a comprehensive V2G energy trading solution, balancing efficiency, security, and privacy.

J. Chandra Priya, G. Nanthakumar, Tanupriya Choudhury, K Karthika

No abstract is available for this record.

Litao Ye, Bin Chen, Shrivastava Shivanshu, Chen Sun · 7 authors

Centralized Dynamic Spectrum Sharing (DSS) faces challenges like data security, high management costs, and limited scalability. To address these issues, a blockchain-based DSS scheme has been proposed in this paper. First, we utilize the ERC4907 standard to mint Non-Fungible Spectrum Tokens (NFSTs) that serve as unique identifiers for spectrum resources and facilitate renting. Next, we develop a smart contract for NFST auctions, ensuring secure spectrum transactions through the auction process. Lastly, we create a Web3 spectrum auction platform where users can access idle spectrum data and participate in auctions for NFST leases corresponding to the available spectrum. Experimental results demonstrate that our NFST, designed according to the ERC4907 standard, effectively meets users' secure and efficient DSS requirements, making it a feasible solution.

Xu Li, Chonggang Wang, Robert Gazda

Distributed ledger technology, with its multitude of advantages including immutability, transparency, decentralization, and security, has excellent potential to promote and even revolutionize future 6G mobile networks. Large-scale distributed ledger deployment within or for mobile networks relies on distributed ledger-focused standards to facilitate and ensure interoperability. The European Telecommunications Standards (ETSI) Industry Specification Group (ISG) on Permissioned Distributed Ledger (PDL) develops PDL-related standards, targeting various application verticals, especially within the Information and Communications Technology (ICT) domain. This article aims to give an overview of ETSI ISG PDL and describes selected PDL standards, which have synergies with future 6G mobile networks.

J. Gissing, Carsten Brockmann

In wireless sensor networks (WSN), a large share of the energy demand arises from wireless communication, especially in wide area networks where transmission distances are at the scale of kilometers.Ensuring reliability of communication links while optimizing energy demand requires heterogeneous radio configurations throughout the network demanding for an automated process for identifying suitable transceiver settings in order to mitigate the effort of manual configuration during deployment.Furthermore, wireless links are susceptible to dynamic influences such as environmental conditions and interference from concurrent channel usage, rendering static radio configuration impractical.Therefore, autonomous organization and self-configuration of wireless communication networks, such as transmission parameter optimization, drastically reduce cost and effort for installation and maintenance of large-scale sensor systems.Such dynamic adaptive behavior can be achieved by local execution of decentralized methods that enable decision-making at the network edge, while also inherently offering advantages such as enhanced system robustness and scalability.In this work, we present a method that exemplifies this approach and experimentally evaluate its performance on real hardware.The adaptive algorithm optimizes the transmitter configuration of a LoRa transceiver by employing a model-free reinforcement learning approach based on an actor-critic setup using a parameterized stochastic policy and state-value function approximation.Experimental results show that the approach surpasses a standard approach in terms of long-term energy demand.Furthermore, the method's capability of adapting to dynamic wireless channels is demonstrated.

Xiang Shao, Ping Cao, Shuo Wang, Wei Wang · 6 authors

Dynamic spectrum sharing (DSS) has been recognized as a promising solution to meet the spectrum requirement in future wireless networks. To enhance the security and efficiency of DSS, in this paper, we propose a Non-Fungible Token (NFT) enabled spectrum sharing framework, which maps spectrum resource blocks into NFTs. Firstly, we propose a method for confirming the ownership and authenticity of resource blocks, leveraging the uniqueness of NFT. Furthermore, to facilitate spectrum sharing, we propose an NFT enabled combination auctions scheme, which is solved by an improved iterative greedy allocation algorithm. Through simulations, we find that the proposed algorithm can improve the total revenue of spectrum provider and the utilization of spectrum resources.

Shuo Wang, Chen Sun

As the scarcity of spectrum resources, especially in mid-band (1 to 6 GHz), becomes more significant in beyond 5G and 6G era, spectrum sharing is promising to solve this problem. Various spectrum sharing approaches have been proposed and standardized, such as centralized geolocation database. The emergence of blockchain technology provides a great solution to enhance spectrum sharing technology in a decentralized way. With blockchain technology, trust can be established among multiple public or private wireless networks owned by different operators. Moreover, decentralized ledgers can reduce the number of transactions and validation processes executed by each node, thereby improving spectrum trading efficiency. In this article, we summarize the standardization progress of spectrum sharing and the application of blockchain in wireless communications. Then, we investigate the key issues encountered by blockchain-based spectrum sharing and propose potential solutions to these problems. Finally, we present future research directions for blockchain-based dynamic spectrum sharing.

W. Wang, Youping Zhao

In this letter, a layered multi-chain spectrum blockchain architecture is proposed for Space-Air-Ground Integrated Network (SAGIN) to significantly reduce system overhead and aggregated interference. Considering the dynamic characteristics of SAGIN, nodes can make hand off between different blockchains based on the interference conflict graph to maintain aggregated interference below the threshold. To further improve spectrum utilization while avoiding harmful interference caused by spectrum trading in SAGIN, a spectrum trading mechanism is proposed, which jointly considers spectrum pricing, deployment location, and transmit power optimization. Simulation results verify the effectiveness of the proposed spectrum blockchain architecture and trading mechanism.

Kuna Venkateswararao, Pravati Swain

Summary Small cell networks can fulfill the increasing demandfor the high data rate of wireless applications. Energy efficiency is an important design parameter of the ultra dense small cell network (UDSCN). The sleeping strategy of small base stations (s‐BSs) is used to enhance the network's energy efficiency. An efficient sleeping strategy of s‐BSs is required while preserving users' quality of service (QoS). The idle s‐BSs can be switched to sleep mode. This paper proposes a blockchain‐enabled solution for the sleeping strategy of s‐BSs. Here, a blockchain‐enabled small cell network is created between the s‐BSs. The network is decentralized, which eliminates the workload of the macro base station (MBS). The proposed network architecture is enabled as a decentralized network through blockchain. The blockchain provides distributed control over the s‐BS operations through a smart contract. Here, smart contracts act as distributed self organizing network features to handle self‐transactions among small cells for switching off s‐BSs in the network. All the software logic required to perform s‐BS operations is written in a smart contract using Ethereum. The proposed solution improves energy efficiency and enables the ultra dense small cell network to be decentralized.

Faisal Tariq, Muhammad R. A. Khandaker, Imran Shafique Ansari

This chapter provides an expert view on the most trending research directions that will likely shape the technological changes needed for the sixth generation (6G) mobile communication systems for the next decade. The notion of collective artificial intelligence (AI), in contrast to the hype of using conventional AI or machine learning methods in wireless systems, is a revolutionary element in 6G. Blockchain technology will likely play a major role in securing and authenticating future communication systems, thanks to the inherent advantages of the distributed ledger technology. While the technologies are expected to provide the technological leaps required for the speculative 6G vision, there are many challenges researchers and engineers will need to address in order to harvest full benefits of 6G. The chapter also presents an overview of the key concepts discussed in this book.

Lorena Chinchilla-Romero, Jonathan Prados-Garzon, Pablo Muñoz, Pablo Ameigeiras · 5 authors

Multi-Wireless Access Technology (WAT) Radio Access Networks (RANs) are becoming a key enabler in 5G and beyond networks due to the public spectrum scarcity, the level of signal confinement and security offered by some wireless technologies (e.g., Light Fidelity (Li-Fi)), and the reduction of the deployment and operational costs. For instance, Wireless Fidelity (Wi-Fi) technology is cheaper and easier to manage than 5G, and leveraging their already deployed infrastructures contributes to capital expenditures saving. Developing autonomous radio resource provisioning (RRP) solutions is fundamental to cost-effectively achieve the zero-touch management in private 5G networks while fulfilling the service requirements. However, modelling the Key Performance Indicators of the radio interface in 5G and beyond is a complex task that requires high-domain knowledge. Furthermore, the resulting models, as well as solving the respective RRP optimization problem using exact methods usually offer a high computational complexity, especially in multi-WAT scenarios. In order to cope with these issues, in this work, we propose an initial design of a Deep Reinforcement Learning-assisted solution for the RRP in a multi-WAT private 5G network. Furthermore, we contex-tualize the solution in the Open RAN architecture framework. A simulation-based proof-of-concept validates the proposal’s proper design and operation considering a realistic private 5G network scenario.