A large number of mobile multimedia terminals are prominent features of smart cities. Device-to-device (D2D) communication takes advantage of the limited bandwidth resources of cellular networks to accommodate more mobile devices. However, when D2D pairs reuse cellular users channels, serious interference leads to energy consumption, which dissatisfies the requirements of green communication. This study focuses on energy efficiency maximization of D2D communication under the constraints of both D2D pairs and cellular users quality of service (QoS). The formulated resource allocation problem is NP-hard, which is usually difficult to solve within polynomial time. To make the problem easy to handle, we divide it into power control and channel allocation sub-problems. In particular, we propose a power control algorithm based on LambertWfunction to maximize the energy efficiency of a single D2D pair. The preference values of D2D pairs and cellular users are calculated using the power control results, respectively. A channel allocation scheme based on Gale-Shapley algorithm utilizes preference values to match two sides, which aims at maximizing the signal to interference plus noise ratio (SINR) of cellular users and the energy efficiency of D2D pairs. Simulation results show that the proposed algorithm could not only guarantee the transmission rate of cellular users, but also improve the system and D2D pairs energy efficiency.

The increase in popularity of vehicles encourages the development of smart cities. With this advancement, vehicular ad-hoc networks, or VANETs, are now frequently utilized for inter-vehicular communication to gather data regarding traffic congestion, vehicle location, speed, and road conditions. Such a public network is open to various security risks. Overall, protecting personal information on VANET is a vital responsibility. The integration of fog computing and VANETs has gained significant importance in recent years, driven by advancements in cloud computing, Internet of Things (IoT) technologies, and intelligent transportation systems. However, ensuring secure communication in fog-based VANETs remains a major challenge. To overcome this challenge, we introduce a novel authenticated key agreement protocol that achieves mutual authentication, generates a secure session key for secret communication, and provides privacy protection without the use of bilinear pairing. We rigorously prove the security of our proposed protocol, which is designed specifically for fog-based VANETs, and has been shown to meet their stringent security requirements. Moreover, we performed formal and informal analysis that shows our proposed protocol is highly efficient,our protocol’s computational and communication overhead are lower than those of other relevant protocols by 45.570% and 29.432%, respectively. Finally we use NS-3 simulation to prove that our proposed algorithm is a practical and scalable solution for secure communication in fog-based VANETs.

The pilot contamination caused by sharing the non-orthogonal pilots among users is considered to be a bottleneck of the massive multi-input multi-output (MIMO) systems. This paper proposes a pilot scheduling scheme based on the degradation to address this problem. Through computing the degradation of the users, the proposed scheduling assigns the optimal pilot sequence to the user who suffers from the greatest degradation in a greedy way. Moreover, the proposed scheme is further optimized with an extra set of orthogonal pilot sequences, which is called pilot scheduling scheme based on user grouping. Simulation results show that the target cell’s achievable sum rate of the proposed scheme is much higher than the random pilot scheduling (RPS) and the smart pilot assignment (SPA) schemes; also, our scheme can reduce the impact of shadowing fading on the target cell’s achievable sum rate effectively.

The intellectual and immense attainment of a smart city and auto-mobile vehicles are gradually growing. This growth drives Vehicular Ad-Hoc Network (VANET), a broadly operated complex network for inter-vehicular transmission to acquire information relevant to the vehicle location, road condition, traffic congestion, and speed. Generally, this information is procured through an open-source communication, which is susceptible to various security threats. In broad terms, the privacy of data in VANET is considered an imperative task. In this regard, many authentication protocols are formerly initiated for VANET. Most of these protocols are precarious owing to eavesdropping, replay, and impersonation attacks, etc. Furthermore, most existing protocols operates on enormous communication and computation rate, which turns them inadequate for VANET. This paper exhibits a lightweight privacy-preserving authentication protocol for $n$ number of vehicles in VANET using the physical unclonable function (PUF) technique, and offers efficient and secure communication via public channels. Moreover, we evaluate our protocol formally and informally, showing that it is scalable, lightweight, and safe compared to formerly protocols. The rate of computation and communication is less than most related protocols. We also simulate the proposed scheme using the NS-3 simulator to measure its various network performance parameters. As a result, it is apparent through the beheld statistics that the presented protocol is beyond practical, efficient, and reliable for the secure dissemination of information in VANET.

In this paper, we study the distributed cooperative spectrum sensing in heterogeneous cognitive radio networks, where each secondary user (SU) adopts a different spectrum sensing algorithm and experience a different channel environment. To solve the spectrum sensing problem, we propose a fusion rule based on dynamic grouping, which can be used in the mobility of the primary user and SUs. By introducing a grouping parameter, the proposed algorithm can realize the dynamic grouping of SUs. The SUs in group-1 will not be able to participate in the cooperation, and the SUs in groups-2 and groups-3 have different weighting factors. The proposed fusion rule is only required to process the independent decision result of each SU, which significantly reduces the data transmission overhead and processing delay. The simulation results show that the proposed fusion rule can effectively improve the dynamic grouping of SUs and fuse detection information, and outperform the OR rule, AND rule, equal gain combining, and maximum signal-to-noise ratio under the same conditions.

Mobile edge computing (MEC), which sinks the functions of cloud servers, has become an emerging paradigm to solve the contradiction between delay-sensitive tasks and resource-constrained terminals. Task offloading assisted by service caching in a collaborative manner can reduce delay and balance the edge load in MEC. Due to the limited storage resources of edge servers, it is a significant issue to develop a dynamical service caching strategy according to the actual variable user demands in task offloading. Therefore, this paper investigates the collaborative task offloading problem assisted by a dynamical caching strategy in MEC. Furthermore, a two-level computing strategy called joint task offloading and service caching (JTOSC) is proposed to solve the optimized problem. The outer layer in JTOSC iteratively updates the service caching decisions based on the Gibbs sampling. The inner layer in JTOSC adopts the fairness-aware allocation algorithm and the offloading revenue preference-based bilateral matching algorithm to get a great computing resource allocation and task offloading scheme. The simulation results indicate that the proposed strategy outperforms the other four comparison strategies in terms of maximum offloading delay, service cache hit rate, and edge load balance.