Millimeter-wave (mmWave) communication is one of the key enablers for 5G systems as it provides larger system bandwidth and the possibility of packing numerous antennas in a small form factor for highly directional communication. In order to materialize the potentially very high beamforming gain, the transmitter and receiver beams need to be aligned. Practically, the Angle-of-Departure (AoD) remains almost constant over numerous consecutive time slots, which presents a state-dependent channel with memory. In addition, the backscatter signal can be modeled as a (causal) generalized feedback. The capacity of such channels with memory is generally an open problem in information theory. Towards solving this difficult problem, we consider a ``toy model'', consisting of a binary state-dependent (BSD) channel with in-block memory (iBM) [1] and one unit-delayed feedback. The capacity of this model under the peak transmission cost constraint is characterized by an iterative closed-form expression. We propose a capacity-achieving scheme where the transmitted signal carries information and meanwhile uniformly and randomly probes the beams with the help of feedback.
翻译:毫米波( mmWave) 通信是5G系统的关键助推器之一,因为它提供了更大的系统带宽,并且有可能将许多天线以小的形式包装成一个高度定向通信的小型因素。为了实现潜在的甚高波成形的增益,发射机和接收机的光束需要对齐。实际上,在多个连续的时段中,AoD(AoD) 环离器(AoD) 仍然几乎保持不变, 连续无数个时段, 显示一个以记忆为依存的频道。 此外, 后散射信号可以模拟成一个( 闭式) 通用反馈。 这些频道的内存能力在信息理论中一般是一个开放的问题。 为了解决这一难题, 我们考虑一个“ 托伊特模式 ”, 由内存( iBM) [ 1 和 一个单位延迟反馈组成的双状态( BSD) 频道组成。 这个模式在最高峰传输成本限制下的能力以迭式的封闭式表达方式为特征。 我们提议一个能力配置机制, 传输信号携带信息, 同时以统一和随机探测的反馈来帮助。