利用基于前导的探测提高多通道ALOHA的吞吐量
On Improving Throughput of Multichannel ALOHA using Preamble-based Exploration
摘要：
机器类型通信（MTC）已经被广泛研究以提供物联网（IoT）中的设备和传感器的连接。由于稀疏的活动，随机访问，例如，ALOHA用于MTC以降低信令开销。本文提出了在MTC系统中采用多信道ALOHA探测的方法，在发送数据包之前先发送前导码，最大吞吐量可以提高2 - exp（-1）= 1.632倍。在所提出的方法中，基站（BS）需要向活动用户发送反馈信息，以告知在多个信道中发送的前导码的数量，其可以如在压缩随机接入中那样被可靠地估计。稳态分析也进行了快速重试，这表明，数据包碰撞的概率变得较低，因此，延迟中断概率大大降低了轻负载系统。仿真结果也证实了分析结果。
英文摘要：
Machine-type communication (MTC) has been extensively studied to provide connectivity for devices and sensors in the Internet-of-Thing (IoT). Thanks to the sparse activity, random access, e.g., ALOHA, is employed for MTC to lower signaling overhead. In this paper, we propose to adopt exploration for multichannel ALOHA by transmitting preambles before transmitting data packets in MTC, and show that the maximum throughput can be improved by a factor of 2 - exp(-1) = 1.632, In the proposed approach, a base station (BS) needs to send the feedback information to active users to inform the numbers of transmitted preambles in multiple channels, which can be reliably estimated as in compressive random access. A steady-state analysis is also performed with fast retrial, which shows that the probability of packet collision becomes lower and, as a result, the delay outage probability is greatly reduced for a lightly loaded system. Simulation results also confirm the results from analysis.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
