We consider the problem of dynamically optimizing a multiple-input multiple-output (MIMO) wireless waveform in a given potentially heavily utilized fixed frequency band with applications in near-field or far-field autonomous machine-to-machine communications. In particular, we find the transmitter beam weight vector and the pulse code sequence that maximize the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum SINR joint space-time receiver filter. We propose and derive two novel model-based solutions: (a) Disjoint, space first (transmit weight vector) then time (pulse code sequence) waveform optimization and (b) jointly optimal transmit weight vector and pulse code sequence optimization (a mixed integer programming problem.) The proposed formally derived algorithmic solutions are studied in extensive simulations under varying waveform code length, near-field/far-field and spread-spectrum/non-spread-spectrum interference, in light and dense interference scenarios. Our findings highlight the effectiveness of the described methods compared to static conventionally designed MIMO links and the remarkable ability of the joint space-time optimized waveforms to avoid heavy interference.

中文翻译：

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自优化近场和远场 MIMO 发射波形


我们考虑在近场或远场自主机器对机器通信中的应用中，在给定的可能大量使用的固定频带中动态优化多输入多输出（MIMO）无线波形的问题。特别是，我们找到了使最大 SINR 联合空时接收机滤波器输出处的信号与干扰加噪声比 (SINR) 最大化的发射机波束权重向量和脉冲编码序列。我们提出并推导了两种新颖的基于模型的解决方案：(a) 不相交、空间优先（发射权重向量）然后时间（脉冲码序列）波形优化和 (b) 联合最优发射权重向量和脉冲码序列优化（混合整数）编程问题。）在不同波形码长、近场/远场和扩频/非扩频干扰、轻干扰和密集干扰场景下，对所提出的形式推导的算法解决方案进行了广泛的模拟研究。我们的研究结果强调了所描述的方法与静态传统设计的 MIMO 链路相比的有效性，以及联合时空优化波形避免严重干扰的卓越能力。