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arXiv 0908.1264cs.ITmath.IT
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相关衰落信道的反馈自适应训练

Adaptive Training for Correlated Fading Channels with Feedback

Manish Agarwal, Michael Honig, Baris Ata

摘要:

我们考虑通过时间选择性,相关(一阶马尔可夫)瑞利衰落信道的平均功率约束的数据传输。在接收机处利用导频信号估计信道,并且将该估计反馈给发射机。该估计用于相干解调,并调整数据和导频功率。我们明确地确定了最佳的导频和数据功率控制策略在连续时间限制的信道状态演变为一个Ornstein-Uhlenbeck扩散过程,并估计由一个卡尔曼滤波器在接收机。最优导频策略在零和最大(峰值约束)值之间切换("bang-bang“控制),并且在低信噪比(等效地,大带宽)下近似于最优离散时间策略。切换边界是根据系统状态(估计的信道均值和相关的误差方差)定义的,并且可以显式计算。在最优策略下,发射机通过在信道衰落时降低训练功率来节省功率,从而提高数据率。数值结果表明,由于自适应训练方案的反馈,相对于常数(非自适应)的训练,这并不需要反馈的可实现的速率显着增加。增益在相对低的SNR和快速衰落时更明显。通过Monte Carlo模拟进一步验证了结果。

英文摘要:

We consider data transmission through a time-selective, correlated (first-order Markov) Rayleigh fading channel subject to an average power constraint. The channel is estimated at the receiver with a pilot signal, and the estimate is fed back to the transmitter. The estimate is used for coherent demodulation, and to adapt the data and pilot powers. We explicitly determine the optimal pilot and data power control policies in a continuous-time limit where the channel state evolves as an Ornstein-Uhlenbeck diffusion process, and is estimated by a Kalman filter at the receiver. The optimal pilot policy switches between zero and the maximum (peak-constrained) value (``bang-bang'' control), and approximates the optimal discrete-time policy at low Signal-to-Noise Ratios (equivalently, large bandwidths). The switching boundary is defined in terms of the system state (estimated channel mean and associated error variance), and can be explicitly computed. Under the optimal policy, the transmitter conserves power by decreasing the training power when the channel is faded, thereby increasing the data rate. Numerical results show a significant increase in achievable rate due to the adaptive training scheme with feedback, relative to constant (non-adaptive) training, which does not require feedback. The gain is more pronounced at relatively low SNRs and with fast fading. Results are further verified through Monte Carlo simulations.

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