In vehicular ad hoc networks (VANETs), beacon broadcasting plays a critical role in improving road safety and avoiding hazardous situations. How to ensure reliability and scalability of beacon broadcasting is a difficult and open problem, due to high mobility, dynamic network topology, hidden terminal, and varying density in both the time and location domains. In this paper, wireless resources are divided into basic resource units in the time and frequency domains, and a distributed and adaptive reservation based MAC protocol (DARP) is proposed to solve the above problem. For decentralized control in VANETs, each vehicle's channel access is coordinated with its neighbors to solve the hidden terminal problem. To ensure the reliability of beacon broadcasting, different kinds of preambles are applied in DARP to support distributed reservation, detect beacon collisions, and resolve collisions. Once a vehicle reserves a resource unit successfully, it will not release it until collision occurs due to topology change. The protocol performance in terms of access collision probability and access delay are analyzed. Based on the analysis, protocol parameters, including transmission power and time slots duration, can be adjusted to reduce collision probability and enhance reliability and scalability. Using NS-3 with vehicle traces generated by simulation of urban mobility (SUMO), simulation results show that the proposed DARP protocol can achieve the design goals of reliability and scalability, and it substantially outperforms the existing standard solutions.

To support emerging vehicular applications such as autonomous driving, the reliability of beacon broadcasting becomes an indispensable issue which is also difficult given the highly dynamic topology and vehicle density. For the territories which are not covered with communication infrastructure, controlling and scheduling in a centralized way may not be applicable. Therefore, vehicle-to-vehicle (V2V) ad hoc communication is promising to address the ubiquitousness coverage concern. In this paper, a distributed network coding-based medium access control protocol (NC-MAC) is proposed to support V2V beacon broadcasting. We combine the preamble-based feedback mechanism, retransmissions, and network coding together to enhance broadcasting reliability. Extensive simulations are given to show the performance gain of the NC-MAC protocol compared to the existing 5G cellular vehicle-to-everything (C-V2X) MAC protocol in a wide range of scenarios.

Vehicle-to-everything (V2X) technology has been proposed as a leading step toward road safety improvement and intelligent transportation systems, and these vehicular-related applications rely on reliable ways of communication. For the regions which are not covered by communication infrastructure or deployment of centralized controllers are not straightforward, vehicle-to-vehicle (V2V) communication is a potential solution. Reliability is crucial in vehicular ad hoc networks (VANETs) from beacon broadcasting and security aspects. Group-casting and applying multi-hop communication can ensure reliability in V2X systems. In this paper, a distributed grouping and network coding-assisted medium access control protocol (GNC- MAC) is proposed to support reliable group-casting. We propose a new grouping protocol by combining preamble-based feedback mechanism, multi-hop communication, and network coding to improve group-casting reliability. Extensive simulations have been conducted to show the performance gain of the GNC- MAC protocol compared to the existing 5G cellular vehicle-to- everything (C-V2X) MAC protocol in a wide range of scenarios.

Reliable and scalable wireless transmissions for Internet of Vehicles (IoV) are technically challenging. Each vehicle, from driver-assisted to automated one, will generate a flood of information, up to thousands of times of that by a person. Vehicle density may change drastically over time and location. Emergency messages and real-time cooperative control messages have stringent delay constraints while infotainment applications may tolerate a certain degree of latency. On a congested road, thousands of vehicles need to exchange information badly, only to find that service is limited due to the scarcity of wireless spectrum. Considering the service requirements of heterogeneous IoV applications, service guarantee relies on an in-depth understanding of network performance and innovations in wireless resource management leveraging the mobility of vehicles, which are addressed in this article. For single-hop transmissions, we study and compare the performance of vehicle-to-vehicle (V2V) beacon broadcasting using random access-based (IEEE 802.11p) and resource allocation-based (cellular vehicle-to-everything) protocols, and the enhancement strategies using distributed congestion control. For messages propagated in IoV using multihop V2V relay transmissions, the fundamental network connectivity property of 1-D and 2-D roads is given. To have a message delivered farther away in a sparse, disconnected V2V network, vehicles can carry and forward the message, with the help of infrastructure if possible. The optimal locations to deploy different types of roadside infrastructures, including storage-only devices and roadside units with Internet connections, are analyzed.

The wide range of Internet-of-Things applications has increased the number of connected devices massively. This growth may cause more contention in accessing the channel, challenging the legacy IEEE 802.11. In the IEEE 802.11ah standard, the grouping technique is exploited to make the stations (STAs) compete in a group to mitigate the contention. However, how to group the STAs in the network is still an open issue. In this paper, we propose a new strategy to group STAs in a dense network to address the above issues. We apply the MaxMin fairness criterion to the STAs' throughput to increase the overall network's performance with better fairness. Formulation of the problem results in a non-convex integer programming optimization problem which avoids hidden terminals opportunistically. As solving the optimization problem is difficult and time consuming, we apply the Ant Colony Optimization method to the problem to find the solution. Extensive simulations have been conducted to validate the solution. The proposed approach can achieve approximately up to 40% gain in the total throughput, 37% gain in the minimum per-STA throughput in the network, and 11% reduction in the number of hidden terminals compared to the existing strategies such as K-means.

We study the computation resource management problem in mobile edge-cloud computing networks. Mobile edge servers shall first satisfy the computation requirements of mobile users and Internet of Things (IoT) devices, and then wholesale redundant computation resources to the cloud networks to maximize their profit. Due to the coarse time granularity of wholesales, computation resource buyback may happen occasionally to deal with traffic bursts. Thus, the mobile edge servers need to make a tradeoff between the wholesale profit and the buyback cost. In this paper, the computation resource management problem is modeled as profit maximization. To solve this problem, we first analyze the relationship among the reserved computation resources, the computation tasks of mobile users and IoT devices, and the buyback cost. Then, we design an efficient wholesale scheme to determine the amount of the wholesaled computation resources, by which the total expected profit of the mobile edge server can be maximized. Given the reserved computation resources, we also propose a fast-convergent realtime buyback scheme for mobile edge servers to minimize the buyback cost. Finally, the simulation results show that our proposed efficient wholesale and buyback scheme can increase the total profit while guaranteeing the computation delay of all the computation tasks, especially when the computation workloads are time-varying.

With the rapid development of mobile Internet and urban constructions, high-volume and dynamic indoor communications bring challenges to cellular systems. High penetration loss and deep shadowing channels of indoor users may substantially degrade the transmission efficiency and system throughput. To address this issue, this paper proposes a solution using Floating Relay (FR) given the mature technologies of unmanned aerial vehicle (UAV). We target the undesirable channel conditions of indoor users, introduce the FR into the cellular system to improve transmission efficiency and maximize system throughput. Considering the capacity limit of the FR's back-haul link and the maximum transmission power of each user, an optimization problem is formulated to maximize the system throughput. The optimal power allocation strategy is then obtained for each user, and two effective online 3-D placement algorithms are proposed for the FR to approach the optimal location in the unpredictable and predictable scenarios, respectively. Extensive simulations are conducted. The achieved maximum system throughput, convergence rate, and accumulated throughput are used to evaluate the proposed algorithms. According to the comparisons between the two proposed algorithms and with off-line schemes, they show superiorities in their targeted scenarios, respectively.

The rapid development of the Internet of Things has brought new challenges to cellular networks with super-dense devices and deep-fading channels. These challenges may substantially decrease the transmission efficiency and increase the device's power consumption, especially in the uplink. A pressing issue is to improve enhanced Node B's (eNB) scheduler considering a large number of users. In this paper, a semi-centralized cooperative control method is proposed for the cellular uplink transmissions, where the user equipment (UE) relays are randomly selected according to a certain density decided by the eNB. Two specific cooperative schemes based on device-to-device (D2D) communications are proposed, which are the random UE relay scheme and the one further applying network coding. The D2D interference is considered and modeled based on stochastic geometry. The proposed schemes are analyzed based on two distinct traffic models, i.e., the machine type communications traffic with the small-data feature and the full-buffer traffic. Extensive Monte Carlo simulations have been conducted for the small-data traffic and the closed-form theoretical results have been derived for the full-buffer traffic. Performance gains are achieved in various scenarios and the comparisons between two cooperative schemes are made as well. The results provide an important guideline for the eNB to determine how to select and configure cooperative D2D communication for uplink.

With the rapid development of the Internet of Things, it is pressing to improve wireless transmission efficiency, especially for machine type communications, due to the limited wireless spectrum. In this paper, we propose a downlink transmission scheme leveraging cooperative device-to-device (D2D) communications and network coding, which can largely reduce the cellular resource consumption and the total energy consumption. In the proposed scheme, the base station generates and broadcasts linear combinations based on the packets requested by different user equipments (UEs) until at least one mature UE can recover all the original packets. Then, a selected mature UE broadcasts new linear combinations based on the recovered original packets to neighbors via D2D until all UEs can decode their packets. A feasible and backward-compatible system design including the necessary revisions on the protocol stack based on the current cellular system architecture is also provided. Then, the closed-form probability mass functions of transmission times for both cellular and D2D transmissions are derived, where the error rates in both cellular and D2D transmissions have been considered. The feedback load is also analyzed. Simulation results with different block error rate (BLER) settings are given, which can be used as references for the cellular network to decide the target BLER and adapt the modulation and coding.

Due to the massive growth in the number of wireless devices and their traffic, the problem of sharing channel access has become much severe in wireless networks. Group Synchronized Distributed Coordination Function (GS-DCF) was introduced in the IEEE 802.11ah standard to group users and give each group a Restricted Access Window (RAW) to compete in. However, how to group users remains an open issue which has a great impact on the network performance. In this paper, an RSS- based grouping strategy is proposed to solve the hidden terminal problem in wireless networks. The analytical and simulation results are then provided to demonstrate the advantages of this scheme over conventional grouping strategies. According to the results, the proposed RSS-based grouping scheme will make the probability of hidden terminal negligible and thus substantially improve the network performance.

The rapid development of the Internet of Things (IoT) has brought big challenges to the traditional cellular networks such as super dense devices and deep fading channels. These new challenges will lead to a significant transmission efficiency degradation and increase the device's power consumption, especially in the uplink. A huge pressure will be also imposed to the enhanced Node B's (eNB) scheduler due to the large number of users. In this paper, a semi- centralized controlled cooperative method is proposed for the uplink cellular transmission, where the User Equipment (UE) relay will be randomly selected according to a certain density decided by the eNB. Two specific cooperative schemes based on the Device-to- Device (D2D) are proposed, which are the random UE relay scheme and the one further combined with the Network Coding (NC). The theoretical analyses for both of them are given and corresponding closed-form results are derived. The D2D interference is considered and modelled based on the stochastic geometry. The performance gains are identified by numerical evaluations in various scenarios and the comparisons between two cooperative schemes are made as well. Also, these results can provide an important guideline for the eNB to determine the optimal density of the UE relays.

With the rapid development of the Internet of Things (IoT), the new challenges brought by the MTC traffic imposed a great pressure to the traditional cellular networks. The new MTC features like small-data transmission, large number of devices and deep fading channels will lead to a significant spectrum efficiency degradation and thus affect the regular Human-to-Human (H2H) communications. In this paper, we proposed a semi-centralized controlled cooperative method to improve the MTC transmission efficiency in the cellular uplink, which is backward- compatible with current LTE/LTE-A protocol and easy for implementation. Two cooperative transmission schemes based on the Device-to-Device (D2D) communications were applied, which are the Random User-Equipment (UE) Relay scheme (RUR) and the Network Coding scheme (NC). The D2D interference was analyzed based on the stochastic geometry, and 2 layers of scheduling were also considered. Intensive simulations were conducted. From the simulation results, a significant gain was achieved by the proposed method especially for the small data traffic. Also, a comparison was made between the RUR and NC schemes, and the suitable scenarios for each scheme can be identified.