Frequency hopping multiple access (FHMA) techniques applied to critical wireless applications often encounter the effects of multiple-access interference (MAI) and follower jamming. The generalized orthogonal FH, which includes no-hit-zone (NHZ) and low-hit-zone (LHZ) FH sequence (FHS), has emerged as a highly promising hopping pattern in quasi-synchronous FHMA systems due to its ability to minimize MAI, but is unable to resist follower jamming attacks. In this paper, we firstly introduce the wide-gap property into an improved NHZ-FHS (i.e., WG-NHZ-FHS), where the frequencies at adjacent time-slots are hopped across a relatively wide gap of bandwidth, so as to address the issues of the MAI and the follower jamming. A general method to generate optimal WG-NHZ-FHS sets satisfying the theoretical bound is proposed. Subsequently, to present the merits of such a hopping pattern, the numerical error-rate performance of the WG-NHZ-FHS set imposed in a quasi-synchronous FHMA system under a follower jamming attacker is derived by using the characteristic function method; in addition, the obtained numerical result is extended to the case of WG-LHZ-FHS as the comparison benchmark. Finally, the numerical analysis and the system simulation results reveal that, compared to the previous types of FHSs, the proposed WG-NHZ-FHS set provides the lower error-rate and higher reliability for critical FHMA applications thanks to its inherent advantages of the MAI-free and the follower jamming suppression.

This paper investigates the file and demand private coded caching system, which ensures that each user learns no information about other users' demands and non-demanded files. By proposing the innovative multi-layered coded caching schemes, this study significantly improves the achievable memory-load tradeoff compared to baseline caching schemes designed by the optimal file private scheme and demand private scheme. In particular, the proposed schemes increase the quantity of achievable memory-load points, markedly reduce the delivery load at low memory regime, and attain a tighter minimal-rate point$(M=N(K-1),\ R=1)$than the baseline schemes.

Nowadays, network slicing (NS) technology has gained widespread adoption within Internet of Things (IoT) systems to meet diverse customized requirements. In the NS based IoT systems, the detection of equipment failures necessitates comprehensive equipment monitoring, which leads to significant resource utilization, particularly within large-scale IoT ecosystems. Thus, the imperative task of reducing failure rates while optimizing monitoring costs has emerged. In this paper, we propose a monitor application function (MAF) based dynamic dormancy monitoring mechanism for the novel NS-IoT system, which is based on a network data analysis function (NWDAF) framework defined in Rel-17. Within the NS-IoT system, all nodes are organized into groups, and multiple MAFs are deployed to monitor each group of nodes. We also propose a dormancy monitor mechanism to mitigate the monitoring energy consumption by placing the MAFs, which is monitoring non-failure devices, in a dormant state. We propose a reinforcement learning based PPO algorithm to guide the dynamic dormancy of MAFs. Simulation results demonstrate that our dynamic dormancy strategy maximizes energy conservation, while proposed algorithm outperforms alternatives in terms of efficiency and stability.

Applying blockchain technology in the Internet of Things (IoT) systems to realize massive data storage is a promising technology, which can eliminate the dependence of IoT on central servers and protect data security effectively. However, in legacy IoT systems, it is hardly to store a complete blockchain at all nodes due to the limited storage space. In order to securely store massive data in the resource-constrained IoT systems, we design a blockchain-assisted distributed storage mechanism, by which multiple nodes collaboratively store a complete blockchain. Meanwhile, we design a deep reinforcement learning (DRL) based algorithm to obtain the optimal block allocation strategy for the collaborative storage. The optimal strategy can maximize the number of storage blocks so as to maximize the utilization of the limited storage space under the premise of meeting the requirements of user query delay and reliability. The simulation results show that compared with the random search algorithm and the policy gradients algorithm, the proposed Deep Q Network algorithm can achieve the maximum number of storage blocks in the same storage space, and the fastest storage speed.

By regularly broadcasting information about the road and weather conditions around vehicles, a Vehicular Adhoc Network (VANET) is expected to improve traffic congestion and relieve traffic pressure. To guarantee the safe communication of vehicles, the security and privacy problems are urgent to be solved in VANETs. Until now, numerous conditional privacy-preserving authentication (CPPA) schemes have been proposed to solve these problems. However, cross-region authentication still not being taken seriously in CPPA scheme. Although several blockchain-based CPPA scheme have being proposed to realize cross-region authentication, there still exist some imperfection such as frequent interactions or unlinkability. Therefore, this paper proposes a novel blockchain-assisted authentication scheme to solve these existing issues. First, we adopt a puncturable pseudorandom function to complete identity authentication of vehicles. Second, a key derivation algorithm is used to achieve unlinkability of messages. Third, we achieve cross-region authentication by taking advantage of the properties of blockchain. The security analysis shows that the proposed scheme is suitable for VANETs.

Cellular network performance depends heavily on the setting of its network parameters. Current practice of parameter setting relies largely on expert experience, which is often suboptimal and time-consuming. Therefore, how to find the optimal parameters automatically is increasingly concerned by network operator. This article proposes a collaborative learning approach to predict the performance of network elements under different parameters based on factorization machine. The proposed approach captures the potential time-aware correlation between network elements and their parameters to boost the accuracy and efficiency of performance prediction. Extensive experiment results demonstrate that the proposed approach can significantly improve the effectiveness of performance prediction, based on a large-scale real-world network dataset collected from a metropolitan LTE network.

In literatures, there are various constructions of frequency hopping sequence (FHS for short) sets with good Hamming correlations. Some papers employed only multiplicative groups of finite fields to construct FHS sets, while other papers implicitly used only additive groups of finite fields for construction of FHS sets. In this paper, we make use of both multiplicative and additive groups of finite fields simultaneously to present a construction of optimal FHS sets. The construction provides a new family of optimal (qm- 1, qm-t-1/r , rqt; qm-t-1/r + 1) frequency hopping sequence sets archiving the Peng-Fan bound. Thus, some FHS sets constructed in literatures using either multiplicative groups or additive groups of finite fields are included in our family. In addition, some other FHS sets can be obtained via the well-known recursive construction through one-coincidence sequence set.

Given a q-ary frequency hopping sequence set of length n and size M with Hamming correlation H, one can obtain a q-ary (nonlinear) cyclic code of length n and size nM with Hamming distance n-H. Thus, every upper bound on the size of a code from coding theory gives an upper bound on the size of a frequency hopping sequence set. Indeed, all upper bounds from coding theory have been converted to upper bounds on frequency hopping sequence sets [1]. On the other hand, a lower bound from coding theory does not automatically produce a lower bound for frequency hopping sequence sets. In particular, the most important lower bound, the Gilbert-Varshamov bound in coding theory, has not been transformed to a valid lower bound on frequency hopping sequence sets. The purpose of this paper is to transform the Gilbert-Varshamov bound from coding theory to frequency hopping sequence sets by establishing a connection between a special family of cyclic codes (which are called hopping cyclic codes in this paper) and frequency hopping sequence sets. We provide two proofs of the Gilbert-Varshamov bound. One is based on a probabilistic method that requires advanced tool- martingale. This proof covers the whole rate region. Another proof is purely elementary but only covers part of the rate region.

In frequency-hopping sequence (FHS) design, the average Hamming correlation is an important performance indicator. In this paper, the average Hamming correlation of low-hit-zone (LHZ) FHS sets, which has not yet been reported previously, is studied. A lower bound on the average Hamming auto-correlation and the average Hamming cross-correlation of LHZ FHS sets is firstly derived. The new lower bound includes the bound for conventional FHS sets derived by Peng et al. as special case. Then a sufficient and necessary condition for an LHZ FHS set with optimal average Hamming correlation is given. Further, a construction of LHZ FHS sets with optimal average Hamming correlation is presented, whose parameters meet the lower bound on the average Hamming correlation of LHZ FHS sets.

In this paper, a general framework of constructing the optimal frequency-hopping sequence (FHS) sets is presented based on the designated direct product. Under this framework, we obtain infinitely many new optimal FHS sets by combining some one-coincide (OC) sequence sets that are newly constructed in this paper with some known optimal FHS sets. Our constructions are also based on extension method. However, our constructions give new and flexible parameters due to the free choice of OC sequence set. As a result, our constructions allow a great flexibility of choosing parameters of FHS sets for a given frequency-hopping spread spectrum system.

To improve the anti-jamming capability and the spectrum efficiency in wireless communication links with high-moving targets, an adaptive beamforming (BF) technique based on antenna array is proposed for FH systems in this paper (i.e., FH-BF systems). A modified FH-BF receiver structure based on uniform circle array (UCA) is designed so as to reduce the steering-vector fluctuation and to improve the convergence rate. The performance of the proposed system, i.e., bit-error-rate (BER), output signal-to-interference-and-noise (SINR) and convergence rate of the adaptive BF, are fully investigated under a serious jamming attack. The simulation results show that the proposed FH-BF system with M-ary FSK signal converges in a reasonably low number of snapshots, which implies that the beamformer can quickly keep up with the position change of high-speed jammers. In addition, the proposed system can significantly offer the additional SINR gains, and improve the anti-jamming capability without any extra cost of bandwidth.

In this paper, the partial Hamming correlation properties of frequency-hopping sequences (FHSs) are discussed. The Peng-Fan bounds on sets of FHSs are generalized to the case of partial correlation. Both individual FHSs with optimal partial autocorrelation and sets of FHSs with optimal partial correlation are presented. The former has more new parameters compared with the known individual FHSs with optimal partial autocorrelation, while the later is obtained in the literature for the first time.