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--- This message came from the IEEE 802.11 Working Group Reflector ---
Ok, I will take care of that if no one else has any objections. Best regards, Xiaofei Clement Wang Principal Engineer | InterDigital T: (631) 622.4028 From: Ziming He <ziming.he@xxxxxxxxxxx>
Hi Xiaofei, Regarding CSI feedback compression use case in pg. 5: I suggest to remove ‘LB-SciFi’ from the above paragraph to avoid confusion, so the paragraph becomes: In [12] , another unsupervised learning technique, Deep Neural Network Autoencoder (DNN-AE) is applied to CSI angle vectors and further compresses the derived angles by leveraging the compression
capability of DNNs. Experimental results show that the algorithm reduces the feedback overhead by 73% and increases the network throughput by 69%, on average. BTW: could you please change my affiliation in pg. 1 from “Samsung Cambridge Solution Center” to “Samsung Cambridge Solution Centre”? Thanks, Ziming From: Xiaofei Wang <Xiaofei.Wang@xxxxxxxxxxxxxxxx>
Dear all, I have uploaded the r10 of 11-22/987, which is the draft AIML TIG technical report. https://mentor.ieee.org/802.11/dcn/22/11-22-0987-10-aiml-aiml-tig-technical-report-draft.doc It contains mostly editorial changes. Many thanks to Stephen, who has so kindly provided a very thorough editorial review of 11-22/987r8.
Since his changes were presented in one of the AIML TIG teleconferences, and there were no objections, I have accepted most of the editorial changes.
There are still a number of comments remaining in the current document, which needs to be addressed by the individual authors.
In addition, I have temporarily removed the structure Problem-AIML Benefits-Summary for each individual use case. Since we will likely have an executive summary, summary/conclusions, we may want to wait a bit to see which structure is preferred
for each use case. But I did add some summary notes for each use case. Please let me know if you have any comments/questions. Best regards, Xiaofei Clement Wang Principal Engineer | InterDigital T: (631) 622.4028 E: Xiaofei.wang@xxxxxxxxxxxxxxxx
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