Parametric Channel Estimation with Short Pilots in RIS-Assisted Near-and Far-Field Communications

The code corresponds to the following paper, accepted for publication in IEEE Transactions on Wireless Communications.

arXiv (Open Access)

Main Functions

  • widebeam.m: To generate Figures 6 and 7 in the paper.
  • wideAlgTest.m: To generate Figures 8 and 9.
  • AlgTestOptimized.m: To generate Figures 10 and 11. It needs to be configured to correspond to either far-field or near-field scenarios.
  • randomwalkRun.m: To generate Figure 12.
  • AzElGraph.m: It plots set of angles that leads to orthogonal beams. Figure 3 in the paper.
  • MLE.m: It is the function that estimate the channel by assuming that it is approximately far-field.
  • MLE3D.m: It estimate the channel by estimating distance and azimuth-elevation pairs. It is work the best for both near field and far-field region.
  • nearFieldChan.m: The function that generate realistic channel based on the propagation distance between user and RIS elements.
  • UPA_BasisElupnew.m: It find all the angle pairs that results in orthogonal beams.
  • UPA_Codebook.m: Generate array responses of the orthogonal angle pairs.
  • ChanParGen.m: generate the channel phase array considering the location of the user and the RIS/BS.
  • MultipleAntennaScenario.m: Generate Figures 13 and 14.
  • CompareHeierarchical.m and CompareHeierarchical_withoutDirect.m: Generate the Figure 15.

Random Walk functions

  • plotTrajectory.m: plot the trajectory of the random walk in the room
  • randomwalk.m: It generate a random walk scenario in a confined room with given size