Integrated sensing and communication (ISAC) in dense multi-cell networks suffers from severe inter-cell interference, degrading both sensing and communication performance. Conventional strategies focus on interference suppression. To address this issue, this paper proposed an interference empowering precoding (IEP) framework that exploits informative inter-cell interference as a distributed sensing resource while protecting communication quality-of-service (QoS) in ISAC. IEP operates on two timescales. In the slow timescale, a lightweight Transformer-based module infers the symbol-level knowledge coefficients of interfering waveforms while per-resource-element adaptation between constructive interference exploitation for sensing and robust suppression for communication is conducted in the fast timescale. A joint optimization problem was formulated to maximize the weighted sum of the communication sum rate and the log-determinant of Fisher Information Matrix with QoS and constructive interference alignment constraints under channel state information uncertainty. The non-convex problem is reformulated as a difference-of-convex program and solved using an alternating Weighted Minimum Mean Square Error and Convex-Concave Procedure algorithm with guaranteed convergence. Simulation results demonstrate that the proposed framework could sub-stantially enlarge the achievable communication-sensing trade-off region. Notably, it achieves approximately 24% reduction in the Position Error Bound and a 21.5% extension in detection range compared to conventional interference suppression schemes, without compromising communication throughput.

Low Earth orbit satellite (LEOS) communications are vital for advancing global connectivity. However, these systems are vulnerable to threats from malicious jamming and the conflict between safety and transmission rates. Covert communication is a promising technology that can reduce the detectability of wireless transmissions at high rates. Therefore, in this paper, we introduced atwo-layer holographicapproach in the LEOS covert communication system based on holographic jamming-parasitic modulation (HJPM) and holographic multiple-input multiple-output (HMIMO). In HJPM, the transmitter superim-poses information signals onto jamming signals, allowing the legitimate receiver to reconstruct useful information from the jamming, effectively hiding the information within the jamming. The HMIMO surface utilizes holographic beamforming to achieve dynamic high-directional gains, thereby enhancing communication for legitimate users while meeting covertness constraints. Additionally, we proposed an optimization algorithm, i.e., Tri-CoHo, that combines elastic parasitic modulation depth with hybrid beamforming to maximize covert transmission rate in LEOS communications. Results showed that our scheme achieves a higher communication performance while maintaining a high level of undetectability compared to benchmarks.

Data Integrity Auditing (DIA) enables users to remotely verify whether their data saved in third-party clouds has been maliciously tampered with or compromised. As an extension of DIA in certificateless cryptography, certificateless DIA (CL-DIA) integrates the merits of conventional public-key cryptography (no key escrow) and identity-based cryptography (no certificates). However, CL-DIA schemes depend on a reliable third-party auditor (TPA) to perform integrity audits, inevitably suffering from performance bottleneck and single-point failure problems. Moreover, almost all current CL-DIA schemes were designed with computationally expensive bilinear pairings. Cryptanalysis demonstrates that the existing unique pairing-free CL-DIA scheme fails to achieve the unforgeable security of auditing proofs. In this work, we put forward a lightweight blockchain-assisted CL-DIA scheme. The scheme achieves DIA through the blockchain instead of a single TPA, thereby overcoming the problems caused by the TPA-based centralized auditing model. Then, by avoiding time-consuming pairing operations and employing edge servers in generating verifiable tags for the uploaded data of users, its performance surpasses previous pairing-based CL-DIA schemes, particularly in terms of computation efficiency. Furthermore, we provide formal proofs in the random oracle model demonstrating that our scheme achieves unforgeability of verifiable tags and auditing proofs, ensures data privacy secrity, and is resistant to collusion attacks between the EN and the CSP. Finally, experimental results show that when auditing 25 file blocks, our scheme only costs 0.29s, which reduces the total time cost of integrity auditing phase by 48.2%-85.5% compared to current pairing-based CL-DIA schemes.

Large language models (LLMs) have shown remarkable abilities by significantly scaling up model size, but this has also greatly increased their computing overhead. Traditional solutions to reduce the overhead are offloading inference tasks to cloud servers. With the evolution of computing power networks, computing resources are increasingly distributed at the network edge, allowing inference tasks to be handled locally. This edge inference can reduce traffic stress on backbone networks from cloud offloading and improve the utilization of heterogeneous edge computing power. However, the challenge is how to balance the gigantic computing workloads of LLMs with the limited computing power at the edge. To overcome this, a mixture-of-depths (MoD) Transformer based tri-parallel distributed approach was introduced. By dynamically allocating computing power to specific positions in the Transformer and parallel computing, this approach maximizes the capabilities of heterogeneous edge nodes to achieve resource-efficient inference. Simulation results showed that the proposal performs best in various edge environments, reducing inference delay by up to 24.3 % and energy consumption by up to 37.5%, respectively.

Searchable public key encryption (SPKE) is a beneficial supplement to traditional public key encryption, which offers a viable method to address the retrieval issue over enciphered data. As a development of SPKE, searchable certificateless encryption enjoys good features of no burdensome certificate management and no key escrow. However, existing searchable certificateless encryption schemes suffer some limitations. Some only support single-keyword search, which often yields inaccurate results. Others enable conjunctive keyword search, which is difficult to cope with data lacking unified keyword fields. In the work, we present a user-friendly certificateless authenticated encryption with field-free multi-keyword search scheme. The proposed scheme eliminates time-consuming operations like bilinear pairing and hash-to-point calculations for data owners and data users. It also enables data users to make multi-keyword searches flexibly on resource-limited mobile devices without concern for keyword orders or positions. As far as we know, it is the first certificateless encryption scheme that supports field-free multi-keyword search. We demonstrate that it has the keyword guessing attack security by formal proofs and show its superior performance by comparisons and experiments. Compared to the state-of-the-art scheme with field-free multi-keyword search, our scheme reduces computation cost for creating a search token and communication cost for sending the search token by about 60% and 56%, respectively.

The growing demand for edge computing is driving the proliferation of wireless computing power infrastructures and poses significant challenges to network energy efficiency (EE). Traditional offloading schemes rely solely on multi-access edge computing (MEC) servers. High-quality communication links and adequate distributed resources are expected to improve EE. Inspired by reconfigurable intelligent surface (RIS) and device-to-device communication technologies, this paper first proposed an edge-end collaborative computing system in RIS-empowered heterogeneous wireless computing power networks. Through resource virtualization, heterogeneous computing powers on MEC servers and nearby devices are unified into resource pools for efficient utilization. In this wireless system, task offloading is closely coupled with channel allocation, power coordination, RIS phase shift design, and base station receive beamforming. To tackle it, this paper suggested a block coordinate descent (BCD)-based framework that decouples the problem into three sub-problems. For each sub-problem, specialized solutions are applied: the Rayleigh quotient maximization and concave-convex procedure for the beamforming and power allocation co-design sub-problem, dimensionality reduction for 3-dimensional task offloading and channel allocation co-pairing sub-problem, and convex optimization for the RIS phase shift control sub-problem. Numerical results showed that the proposed method can outperform benchmark approaches in terms of EE and delay by up to 28.5% and 22.9%, respectively.

Attribute-based signature (ABS) is an attractive variation of digital signature that enables signers to sign messages with fine-grained signature predicates. In ABS, a signer is able to perform signing operations without revealing personal attributes, and verifiers can only confirm that the signature was created by someone with attributes satisfying a specific signature predicate. However, traditional ABS suffers from key exposure, and the compromise of a signer’s signature key results in invalidating all signatures from him/her. To address this problem, forward-secure ABS (FS-ABS) was introduced. Nevertheless, existing FS-ABS schemes have the shortcomings of low policy expressiveness and high computation costs, and thus are not suitable to be employed on mobile devices with limited resources. In this paper, we propose a user-friendly and expressive FS-ABS (UEFS-ABS) scheme that is proven secure in the standard model. The proposed scheme not only supports expressive signature predicates based on the linear secret sharing scheme, but also provides server-aided signature and outsourced verification functions, significantly reducing the workload of user terminals at both signature generation and verification stages. The experiments indicate that compared with the up-to-date FS-ABS scheme, our scheme reduces the computation costs for signature generation (on signers’ devices) and verification (on verifiers’ devices) by about 85% and 68%, respectively. This makes our scheme more suitable for user terminals in mobile computing scenarios.

The forthcoming sixth generation (6G) mobile communication system aims to advance technologies that span and integrate computation and communications. Computing power networks (CPNs) and virtualized radio access networks (vRANs) are regarded as two fundamental techniques to achieve this integration. Network functions of virtualized next-generation Node Bs (vgNBs) are implemented on general-purpose servers to process protocol stacks. The energy consumption of vgNBs accounts for a significant portion of energy consumption. However, the proliferation of computing power nodes results in increased energy consumption in CPNs. Power usage effectiveness (PUE) reflects the efficiency of computing nodes while efficiency of computing power (ECP) is adopted to indicate data rates per computing power unit. In this work, a joint load adjustment and sleep management scheme was designed to maximize ECP while minimizing PUE. The optimization problem was formulated as a mixed integer non-linear programming (MINLP) problem, which is NP-hard. A quantum genetic algorithm (QGA) with non-equal size quantum register was suggested to solve this problem. Simulation results demonstrated that the proposed algorithm could outperform benchmark approaches in terms of convergence speed, ECP, PUE, and computing power consumption. When compared to other methods, the proposed approach could improve ECP and computation energy consumption by up to 19.5% and 21.7%, respectively.

The active reconfigurable intelligent surface (RIS) consists of multiple independently controllable reflective elements, each equipped with a power amplifier (PA). Deploying it in a wireless communication environment allows the amplified signal to be reflected to users, thereby enhancing the performance. However, a large number of independent PAs brings challenges in energy efficiency (EE). To address this issue, we introduced a sub-connected hybrid RIS (SC-HRIS). The SC-HRIS consists of multiple passive and active elements, with active elements organized into groups, each equipped with a dedicated PA. For RIS-assisted downlink multi-user multiple-input single-output systems, we considered joint transmit beamforming and hybrid RIS coefficient design. The EE maximization problem was formulated and solved by fractional programming in conjunction with the block coordinate descent (BCD) method. Simulation results proved that the proposed SC-HRIS could outperform the other RIS approaches in terms of EE.

Ultradense networks (UDNs) are considered to be a key technology that can meet the growing rate requirements caused by the explosion of user equipments (UEs) in the Internet of Things (IoT) applications. The dense deployment of small-cell base stations (SBSs) facilitates the reuse of spectrum resources but also leads to significant interference among adjacent SBSs. Joint transmission (JT) technology can alleviate intercell interference and improve throughput. However, signal processing and backhaul during BS cooperation require additional power consumption, which reduces the energy efficiency (EE) of UDNs. Additionally, the arrival time of received signals from different cooperative BSs at UEs results in asynchronous interference, which poses a significant challenge for JT. To improve EE, we need to determine the clustering strategy and address the interference issue of asynchronous JT. Specifically, the EE-centric (EEC) clustering scheme was proposed based on the maximal independent set of graph theory to determine the SBS clusters. In each cluster, asynchronous gap generation and gap compensation operations were employed to eliminate tail interference of asynchronous JT and compensate for the gap between adjacent received blocks, respectively. This approach effectively mitigated the asynchronous interference at UEs. Simulation results demonstrated that the proposed asynchronous interference cancelations in EEC clusters can significantly improve sum rate and EE compared to other schemes.

Vehicular ad hoc networks (VANETs) serve as the foundation of intelligent transportation systems, aiming to improve communication efficiency and safety among vehicles. With the expanding applications, security and privacy have become apparent, and the large-scale message transmission imposes substantial computation and communication overheads. The technology of aggregate signature can realize message authentication and reduce both the bandwidth and computation costs significantly. In IEEE 802.11p-based VANETs, most existing aggregate signature schemes require roadside units (RSUs) to verify single signatures before calculating aggregate signatures, which is very inefficient. Furthermore, even with a valid aggregated signature, the validity of individual signatures cannot be assured. In this paper, we propose an efficient certificateless aggregate signature scheme, where RSUs do not need to validate single signatures but compute aggregate signature directly. The successful verification of the aggregated signature implies the validity of each individual signature. Additionally, to further protect data security and user privacy, this scheme employs designated verifiers for both individual and aggregate signatures. Both formal and informal security analysis are given, and performance evaluation shows our scheme exhibits lower computation and communication costs, along with more comprehensive security attributes in VANETs.

Orthogonal time frequency space (OTFS) is considered a promising modulation technology for integrated sensing and communication (ISAC) systems, which is robust against Doppler effects in time-frequency doubly-selective channels. However, limited by the communication bandwidth and frame duration, the fractional delay and Doppler problem in OTFS-ISAC systems, that is, the delay and Doppler of the channel are not integer multiples of the resolutions, leading to estimation errors. To help overcome this issue, in this work, we propose an amplitude barycenter calibration (ABC) algorithm, which uses observation points on the integer delay-Doppler grid to calibrate target estimates, thereby providing satisfactory sensing performance without broadening the bandwidth. In addition, the estimation error and Cramér–Rao lower bound of the ABC algorithm were derived by analyzing its sensing performance. The results demonstrated that the proposed ABC algorithm can improve distance and velocity sensing resolution while achieving acceptable communication performance.

Abstract Since futuristic cellular core networks are envisioned to accommodate emerging vertical domain applications with diverse QoS requirements, software‐defined networking (SDN) technology has played a vital role in improving the scalability and flexibility of network management. This paper presents the design and development of a service‐aware transport layer framework in SDN‐enabled cellular core networks. It aims to study and accommodate three typical traffic types: enhanced mobile broadband (eMBB), ultra‐reliable and low latency communications (URLLC), and massive machine‐type communications (mMTC) in optimal path selection. The proposed framework is able to dynamically allocate network resources to corresponding traffic of above types for satisfying the requirements of each identified flow, using a multi‐level queue management mechanism to alleviate the flow dropping problem when the network becomes congested. For experiment and verification, a testbed platform was built to evaluate the functionalities of developed modules, the performance of the diffserv‐based optimal path selection, and the operation of multi‐level queue management. The experiment results demonstrate that the proposed algorithms could obtain a higher accepting ratio than the other ones in different network conditions.