基于星间协作的低轨卫星物联网鲁棒预编码设计

Robust precoding design for inter-satellite cooperation-based low-earth orbit satellite Internet of Things

随着物联网的广泛应用,地面物联网已经难以满足海量广域分布设备的接入需求,亟需研究低地球轨道(low-earth orbit,LEO)卫星物联网(satellite Internet of Things,SIoT).LEO-SIoT网络为了实现全球无缝覆盖,会使用几十颗甚至上千颗低轨卫星组成一个卫星星座,但这也造成了严重的星间干扰.本文提出一种结合非正交多址接入(non-orthogonal multiple acces,NOMA)和多波束预编码技术的LEO-SIoT网络,可以支持海量设备接入并抑制波束间和卫星间干扰.然而,卫星获取的信道状态信息(channel state information,CSI)具有信道误差,导致传统的预编码方法无法起到抑制干扰的作用.因此,本文首先以低轨卫星物联网的总功耗为目标函数,并以物联网设备所需速率阈值的中断概率为约束建立星间联合鲁棒预编码优化问题;其次,利用二阶泰勒展开、伯恩斯坦不等式(Bernstein-type inequality,BTI)和惩罚函数等数学方法将原问题转化为近似等效的二阶锥规划(second-order cone program,SOCP)问题;最后,本文提出了一种鲁棒预编码算法来解决SOCP问题.大量仿真结果证明了该算法的有效性和鲁棒性.

With the widespread application of the Internet of Things(IoT),a large demand for supporting massive access of IoT devices distributed over a large area urges researchers to focus on the low-earth orbit(LEO)satellite IoT(SIoT)network.Due to the high-speed movement of LEO satellites,SIoT is composed of dozens of satellites to thousands of LEO satellites covering the whole world,which inevitably causes inter-satellite interference.Hence,in this paper,we propose an inter-satellite cooperation framework for a SIoT network based on non-orthogonal multiple access(NOMA)and multiple-beam techniques,which can support massive access and reduce interference.However,the satellite cannot catch accurate channel state information(CSI),resulting in residual interference.In this context,we formulate a robust precoding optimization problem based on inter-satellite cooperation to minimize the total power consumption of the LEO SIoT network with outage probability constraints on the rates for the IoT devices.Because the original problem is intractable,we utilize some mathematical tools,e.g.,second-order Taylor expression,Bernstein-type inequality,and penalty function,to obtain an approximate equivalent second-order cone program(SOCP)problem.Then,we propose a robust precoding algorithm to solve the SOCP problem.Finally,numerical results show the impacts of key system parameters and confirm the effectiveness and robustness of the proposed algorithm.