论文标题
通过开槽的Aloha驱动的反向散射通信利用混合动力主动和被动多重访问
Exploiting Hybrid Active and Passive Multiple Access via Slotted ALOHA-Driven Backscatter Communications
论文作者
论文摘要
在常规的反向散射通信(BackCom)系统中,时间划分多访问(TDMA)和频部多访问(FDMA)通常用于多源反向散射,因为它们的实现简单性。但是,随着反向散射设备(BDS)的增殖数量,在传统的集中式控制技术下将有一个高间接头顶,并且用户间协调对被动BDS无法承受,这在现有作品中很少关注并且仍然无法解决。为此,在本文中,我们提出了一个基于插槽的Aloha的随机访问Backcom系统,其中每个BD都是随机选择的,并允许使用一个主动设备共存,以进行混合多重访问。为了挖掘和评估性能,制定了最大值传输速率的资源分配问题,如果选择天线选择,接收光束设计,反射系数调整,功率控制和访问概率确定。为了解决这个棘手的问题,我们首先将目标函数用最大值的形式转换为等效线性,然后将结果问题分解为三个子问题。接下来,具有惩罚函数,连续的凸面近似和线性编程的基于块坐标下降(BCD)的贪婪算法旨在获得可拖动分析的亚最佳解决方案。仿真结果表明,所提出的算法在传输速率和公平性方面优于基准算法。
In conventional backscatter communication (BackCom) systems, time division multiple access (TDMA) and frequency division multiple access (FDMA) are generally adopted for multiuser backscattering due to their simplicity in implementation. However, as the number of backscatter devices (BDs) proliferates, there will be a high overhead under the traditional centralized control techniques, and the inter-user coordination is unaffordable for the passive BDs, which are of scarce concern in existing works and remain unsolved. To this end, in this paper, we propose a slotted ALOHA-based random access for BackCom systems, in which each BD is randomly chosen and is allowed to coexist with one active device for hybrid multiple access. To excavate and evaluate the performance, a resource allocation problem for max-min transmission rate is formulated, where transmit antenna selection, receive beamforming design, reflection coefficient adjustment, power control, and access probability determination are jointly considered. To deal with this intractable problem, we first transform the objective function with the max-min form into an equivalent linear one, and then decompose the resulting problem into three sub-problems. Next, a block coordinate descent (BCD)-based greedy algorithm with a penalty function, successive convex approximation, and linear programming are designed to obtain sub-optimal solutions for tractable analysis. Simulation results demonstrate that the proposed algorithm outperforms benchmark algorithms in terms of transmission rate and fairness.