Khan Izaz Ahmad, Shah Syed Adeel Ali, Akhunzada Adnan, Gani Abdullah, Rodrigues Joel J P C
Department of Computer Science and Information Technology, University of Engineering and Technology (UET), Peshawar 25000, Pakistan.
Department of Computer Science, Bacha Khan University, Charsadda 24420, Pakistan.
Sensors (Basel). 2021 Nov 9;21(22):7431. doi: 10.3390/s21227431.
Effective communication in vehicular networks depends on the scheduling of wireless channel resources. There are two types of channel resource scheduling in Release 14 of the 3GPP, i.e., (1) controlled by eNodeB and (2) a distributed scheduling carried out by every vehicle, known as Autonomous Resource Selection (ARS). The most suitable resource scheduling for vehicle safety applications is the ARS mechanism. ARS includes (a) counter selection (i.e., specifying the number of subsequent transmissions) and (b) resource reselection (specifying the reuse of the same resource after counter expiry). ARS is a decentralized approach for resource selection. Therefore, resource collisions can occur during the initial selection, where multiple vehicles might select the same resource, hence resulting in packet loss. ARS is not adaptive towards vehicle density and employs a uniform random selection probability approach for counter selection and reselection. As a result, it can prevent some vehicles from transmitting in a congested vehicular network. To this end, the paper presents Truly Autonomous Resource Selection (TARS) for vehicular networks. TARS considers resource allocation as a problem of locally detecting the selected resources at neighbor vehicles to avoid resource collisions. The paper also models the behavior of counter selection and resource block reselection on resource collisions using the Discrete Time Markov Chain (DTMC). Observation of the model is used to propose a fair policy of counter selection and resource reselection in ARS. The simulation of the proposed TARS mechanism showed better performance in terms of resource collision probability and the packet delivery ratio when compared with the LTE Mode 4 standard and with a competing approach proposed by Jianhua He et al.
车载网络中的有效通信取决于无线信道资源的调度。在3GPP第14版中有两种信道资源调度类型，即：（1）由eNodeB控制，以及（2）由每辆车执行的分布式调度，称为自主资源选择（ARS）。对于车辆安全应用来说，最合适的资源调度是ARS机制。ARS包括（a）计数器选择（即指定后续传输的数量）和（b）资源重选（指定计数器到期后相同资源的重用）。ARS是一种分散式资源选择方法。因此，在初始选择期间可能会发生资源冲突，此时多辆车可能会选择相同的资源，从而导致数据包丢失。ARS对车辆密度不具有适应性，并且在计数器选择和重选时采用均匀随机选择概率方法。结果，它可能会阻止一些车辆在拥堵的车载网络中进行传输。为此，本文提出了用于车载网络的真正自主资源选择（TARS）。TARS将资源分配视为一个在本地检测相邻车辆所选资源以避免资源冲突的问题。本文还使用离散时间马尔可夫链（DTMC）对计数器选择和资源块重选对资源冲突的行为进行建模。利用该模型的观察结果提出了ARS中计数器选择和资源重选的公平策略。与LTE模式4标准以及Jianhua He等人提出的竞争方法相比，所提出的TARS机制的仿真在资源冲突概率和数据包交付率方面表现出更好的性能。
