A Novel Hybrid Access Point Channel Access Method for Wireless Powered IoT Networks

Author(s):  
Xiaoyu Song ◽  
Kwan-Wu Chin
Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5111
Author(s):  
Youngboo Kim ◽  
Lam Kwon ◽  
Eun-Chan Park

IEEE 802.11ax uplink orthogonal frequency division multiple access (OFDMA)-based random access (UORA) is a new feature for random channel access in wireless local area networks (WLANs). Similar to the legacy random access scheme in WLANs, UORA performs the OFDMA backoff (OBO) procedure to access the channel and decides on a random OBO counter within the OFDMA contention window (OCW) value. An access point (AP) can determine the OCW range and inform each station (STA) of it. However, how to determine a reasonable OCW range is beyond the scope of the IEEE 802.11ax standard. The OCW range is crucial to the UORA performance, and it primarily depends on the number of contending STAs, but it is challenging for the AP to accurately and quickly estimate or keep track of the number of contending STAs without the aid of a specific signaling mechanism. In addition, the one for this purpose incurs an additional delay and overhead in the channel access procedure. Therefore, the performance of a UORA scheme can be degraded by an improper OCW range, especially when the number of contending STAs changes dynamically. We first observed the effect of OCW values on channel efficiency and derived its optimal value from an analytical model. Next, we proposed a simple yet effective OBO control scheme where each STA determines its own OBO counter in a distributed manner rather than adjusting the OCW value globally. In the proposed scheme, each STA determines an appropriate OBO counter depending on whether the previous transmission was successful or not so that collisions can be mitigated without leaving OFDMA resource units unnecessarily idle. The results of a simulation study confirm that the throughput of the proposed scheme is comparable to the optimal OCW-based scheme and is improved by up to 15 times compared to the standard UORA scheme.


2018 ◽  
Vol 7 (1) ◽  
pp. 70-73
Author(s):  
Mihir Laghate ◽  
Paulo Urriza ◽  
Danijela Cabric

Author(s):  
Xiaoying Lei ◽  
Xiangjin Chen ◽  
Seung Hyong Rhee

AbstractVehicular Ad-hoc Networks (VANETs) can improve the road safety by transmitting safety-critical messages such as beacons and emergency messages. IEEE 802.11p VANETs have adopted the carrier sense multiple access with collision avoidance (CSMA/CA) mechanism for the multiple access control. The 802.11p media access control (MAC) protocol, however, can not guarantee the reliability of broadcasting data, since the reception of transmitted messages are not acknowledged. Moreover, the backoff scheme of the 802.11p MAC utilizes a fixed-size contention window for safety message broadcasting, which causes high collision probabilities especially in dense environments. In order to improve such drawbacks, we propose a hybrid access method as follows: Nodes are equipped to reserve time slots for the next round of broadcasting, while unoccupied time slots are preserved for those which have emergency needs. In addition, implicit feedbacks are enabled for detecting collisions incurred during random channel accesses in preserved time slots. We devise a mathematical model which optimally controls the parameters of our scheme while minimizes the cost caused by idle channels and collisions. Extensive simulations show that our mechanism can remarkably improve the performance of VANETs in broadcasting of the safety messages.


Author(s):  
Hong-Sik Kim ◽  
Inwhee Joe

AbstractHybrid access point (HAP) is a node in wireless powered communication networks (WPCN) that can distribute energy to each wireless device and also can receive information from these devices. Recently, mobile HAPs have emerged for efficient network use, and the throughput of the network depends on their location. There are two kinds of metrics for throughput, that is, sum throughput and common throughput; each is the sum and minimum value of throughput between a HAP and each wireless device, respectively. Likewise, two types of throughput maximization problems can be considered, sum throughput maximization and common throughput maximization. In this paper, we focus on the latter to propose a deep learning-based methodology for common throughput maximization by optimally placing a mobile HAP for WPCN. Our study implies that deep learning can be applied to optimize a complex function of common throughput maximization, which is a convex function or a combination of a few convex functions. The experimental results show that our approach provides better performance than mathematical methods for smaller maps.


Sign in / Sign up

Export Citation Format

Share Document