MmWave Channel Estimation with Few-Bit ADCs
The channel capacity with perfect CSIT was studied in our previous work where two methods were proposed to design the input constellation to maximize the channel capacity. It was shown that MIMO precoding provides a substantial performance improvement compared with the no-precoding case (i.e., independent QPSK or Gaussian signaling). To perform such optimization, however, CSI is required at the transmitter. Due to the nonlinearity of quantization, channel estimation with few-bit ADCs is challenging.
We developed channel estimation algorithms for mmWave MIMO systems with few-bit ADCs. In the mmWave channel, there are fewer paths in the channel and large antenna arrays are deployed at the transmitter and receiver. Therefore the channel is ‘sparse’ (but not strictly sparse) in the angular domain as shown in the figure. By exploiting this sparsity, the estimation problem was formulated as a one-bit compressed sensing problem. We presented a solution using the generalized approximate message passing (GAMP) algorithm to solve this optimization problem.
J. Mo, P. Schniter, N. G. Prelcic and R. W. Heath, Jr., “Channel Estimation in Millimeter Wave MIMO Systems with One-Bit Quantization,” 2014 Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Nov. 2014.
The work was supported in part by the National Science Foundation under Grant Nos. NSF-CCF-1319556, NSF-CCF-1018368 and NSF-CCF-1218754.