ATINA: Approximate optimality of treating interference as noise in wireless multiple-input single-output (MISO) antenna networks

预计到2020年，连接的无线设备的数量将超过500亿。因此，系统设计人员面临着管理这些设备相互之间产生的干扰的挑战。这就要求方案，一方面最佳地利用有限的资源，如时间、频率和功率。另一方面，这些方案的计算复杂度需要保持在合理的水平，以便它们可以在实践中部署。因此，计划项目的目标是研究处理干扰的最简单方法之一的近似最优性，即将干扰视为噪声（TIN）。因此，该项目的主要目标是找到TIN关于最大可达速率（即，能力）。为此，我们考虑了一般的软衰落信道与多个天线的不完美的信道状态信息。 为解决这一问题提出的研究方法分为三个工作包，计划为期三年。研究了在单天线软切换信道下，当时延输出为线性确定性函数时，TIN的容量最优性（无噪声设置）的输入。从第一个工作包获得的见解将用于第二个工作包，这是专门的噪声软-此外，在这个工作包中，我们研究了TIN的近似最优性，其中节点配备有多个天线。从这个任务获得的结果突出了缺乏信道知识对TIN的近似最优性的影响，对于多个天线的情况。最后，在工作包3中，我们实现用于跨层评估的系统级模拟器（即，结合调度算法）并在更一般的模型中验证所获得的结果。不同的用户建模方法进行了评估，从静态用户部署开始，后来与移动的用户。除此之外，我们使用系统级模拟器来评估近似最优的TIN的有用的吞吐量（有效吞吐量），这需要考虑到用户协调成本方面所需的反馈。

It is projected that the number of connected wireless devices will exceed 50 billions by 2020. Thus, system designers are confronted with the challenge of managing the resulting interference those devices cause to each other. This calls for schemes, which on one hand utilize the limited resources such as time, frequency, and power optimally. On the other hand, the computational complexity of those schemes needs to be kept at a reasonable level so that they can be deployed in practice. In consequence, the goal of the planned project is studying the approximate optimality of one of the most simple ways dealing with interference, namely treating interference as noise (TIN).Thus, the main objective of the project is to find the necessary andsufficient conditions on the approximate optimality of TIN with respect to the maximum achievable rate (i.e., capacity). To this end, we consider the general soft-handoverchannel with multiple antennas with imperfect channel state information. The proposed research methods for dealing with this problem arestructured in three work packages which are planned for three years.In work package 1, we study the capacity optimality of TIN for thesoft-handover channel with single antenna in which the output of thesetup is a linear deterministic function (noiseless setup) of the input.The insights obtained from the first work package will be used in thesecond work package which is devoted to the noisy soft-handover channel.Moreover, in this work package, we study the approximate optimality of TIN for themore general setup in which the nodes are equipped with multi antennas.The results obtained from this task highlight the effect the lack of channel knowledge on the approximate optimality of TIN for the multiple antenna case.Finally, in work package 3, we implement a system level simulator for the cross-layer evaluation (i.e., in combination with scheduling algorithms) and verification of the obtained results in more general models.Different user modeling methods are evaluated, starting with static user deployment and later on with mobile users. In addition to this, we use the system level simulator to assess the approximateoptimality of TIN in terms of useful throughput (goodput), which takes theuser coordination costs in terms of required feedback into account.