Abstract-Scheduling algorithms are of utmost importance in WiMAX for efficient use of radio resources. A scheduling algorithm should take into account the WiMAX QoS classes and service requirements. It should also provide high throughput. In this paper, we propose a review of scheduling algorithms proposed for WiMAX. We focus on the real-time Polling Service (rtPS) QoS class. NS-2 simulations show interesting results. We highlight a problem that may exist with the WiMAX rtPS QoS class and we provide solutions for it. Simulation results concerning proposed WiMAX schedulers are discussed. We propose an enhancement of the maximum Signal-to-Interference Ratio (mSIR) scheduler, called modified maximum Signal-to-Interference Ratio (mmSIR). We show through extensive simulations that this enhancement provides better mean sojourn time in addition to an improvement in throughput.

WiMAX is a very promising technology. The main promises are the high throughput and the large coverage. As for all new technologies, performance studies are required. The network simulation is considered as a solution to test the performance of technologies and especially the wireless networks. In this paper, we propose a new WiMAX module for NS-2 simulator. This module is based on the NIST implementation of WiMAX [5]. Our contribution consists of the addition of the QoS classes as well as the management of the QoS requirements, unicast and contention request opportunities mechanisms, and scheduling algorithms for the UGS, rtPS and BE QoS classes. Simulation results provide interesting observations about the throughput and mean sojourn time values. Simulation results show that our UGS, rtPS, and BE schedulers are in accordance with the specification of the QoS classes defined in the IEEE 802.16 standard.

Vehicular communication systems have recently attracted a lot of attention because of their potential to improve road efficiency, comfort, and safety. In this paper, we investigate the resource management problem for device‐to‐device–based vehicle‐to‐vehicle communication. A multiobjective radio resource allocation and sharing algorithm is proposed based on a swarm intelligence algorithm called ant colony optimization (ACO). First, for the resource allocation process, three objective functions are formulated to maximize the users' transmission capacity, reduce the mobile transmission power, and minimize the intracell interference. Second, for the resource sharing process, we define two objective functions to optimize the resource utilization and reduce the intercell interference. Finally, a weighted sum method is used to join these objective functions and define one multiobjective optimization problem. The ACO algorithm is used to determine the Pareto optimal solution. Simulation results show that the proposed algorithm performs well and achieves promising performance in terms of network sum rate, packet drop rate, average queuing delay, resource utilization, and mobile's transmission power.

WiMAX/IEEE 802.16 Broadband Wireless Access (BWA) is a very open technology with different possible services that is likely to be widely used in Metropolitan Access Networks in the near future. While the technical aspects of that technology are now quite well established, the economic implications of the introduction of WiMAX technology have received little attention. In this paper, we consider the problem of pricing WiMAX sessions: we propose some simple pricing mechanisms aimed at coping with congestion while maintaining a sufficient quality of service and/or yielding a sufficient revenue to the operator. Our mechanisms are evaluated under a specific model of user preferences and WiMAX situations, and the implications of some parameter choices are observed.

Internet of Things is a promising paradigm that provides the future network of interconnected devices. Device-to-Device (D2D) communication, which is considered as an enabler for vehicle-to-everything applications, has become an emerging technology to optimize network performance. In this paper, we study the Radio Resource Management (RRM) issue for D2D-based Vehicle-to-Vehicle communication. The RRM key role is to assure the proficient exploitation of available resources while serving users according to their quality of service parameters. An Ant Colony Optimization (ACO)-based Resource Allocation (ACORA) scheme is proposed in this paper. Swarm intelligence algorithm ACO is adopted to reduce the computational complexity while realizing satisfactory performance. Simulation results show promising performance of our proposed ACORA scheme. KEYWORDSD2D communication, Internet of Things, radio resource management, software defined networks | INTRODUCTIONInternet of Things (IoT) is an integrated element of future Internet containing existing and evolving networks as well as Internet progress. Conceptually, it could be defined as a global dynamic network infrastructure with self-management and self-configuration capabilities based on interoperable and standard communication protocols. 1 Device-to-Device (D2D) communication is an important part of the IoT, in which devices autonomously communicate and collaborate with each other, share, and forward information without centralized control in a multi-hop way. The ability to collect pertinent information in real time is the key to support the value of IoT, expediting the creation of an intelligent environment. Vehicle-to-Everything (V2X) is based on D2D communication. V2X is an emerging technology that enhances and leverages existing Long-Term Evolution (LTE) network elements and features to assure the communication between vehicles and the infrastructure as well as between vehicles. The attractiveness of this emergent technology is due to its ability to support safety use cases with stringent bandwidth, delay, and reliability requirements. 2 In release 12 3 and release 13 4 of LTE, V2X is introduced as part of the Proximity Services (ProSe). 5 It includes many applications, such as travel information, navigation and driver assistance, payment transactions, fleet management, congestion avoidance, safety, and traffic control.V2X communication consist of different kinds of communications: Vehicle-to-Vehicle (V2V), Vehicle-to-Network (V2N), Vehicle-to-Pedestrian (V2P), and Vehicle-to-Infrastructure (V2I). 6 As V2V communication has elevated density and speed, it introduces several technical challenges especially the latency and reliability requirements. Guaranteeing these Quality of Service (QoS) requirements for V2V services is still a challenge that must be tackled. IEEE 802.11p 7 was the first standard for V2V communication until 2016. The Third Generation Partnership Project (3GPP), introduced in release 14 of LTE, features addressing direct V2V communications. 8,9 The mai...