DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103, which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-7 and 9-16 are rejected under 35 U.S.C. 103 as being unpatentable over US 20230276255 A1 (Iwabuchi), in view of Zhang, Y. and Alkhateeb, A., 2021. Learning Reflection Beamforming Codebooks for Arbitrary RIS and Non-Stationary Channels. arXiv e-prints, pp.arXiv-2109 (Zhang) and in further view of Jiang, J., Wang, X., Sidhu, G.A.S., Zhen, L. and Gao, R., 2019. Clustering-Based Codebook Design for MIMO Communication System. arXiv preprint arXiv:1902.09101 (Jiang).
Regarding Claims 1, 7 and 9:
A control device comprising: a control pattern selection unit configured to select a control pattern for an IRS based on a codebook and a reference value acquired from a target of the IRS, the codebook indicating a correspondence relation between a representative value specified based on the reference value and the control pattern for the IRS; and a control unit configured to control the IRS based on the control pattern, wherein the codebook is generated by clustering a plurality of reference value samples of a target of an IRS into a plurality of clusters, calculating a representative value in each cluster based on reference values clustered in each cluster, calculating a control pattern corresponding to the representative value, and calculating a correspondence relation between the representative value and the control pattern (Iwabuchi: Fig. 1, a system configuration that comprises a base station to communicate to a UE through a dynamic reflector 5-1/5-2 controlled by a reflection control device 6; Figs, 2-10 illustrate various component configurations, methods, and etc.; par. 37, "The reflection direction control device 6 estimates (measures) a position of the wireless terminal 3 on the basis of signals inputted from the dynamic reflector... and estimates the incident direction of radio waves" and par. 80, "The control unit 68 includes a CPU 680 and memory 682, and controls each unit constituting the reflection direction control device 6", which teaches a control unit configured to control an IRS based on a control pattern and an acquired reference value; par. 76, "the phase calculation unit 66 may calculate the mutual distance between the wireless terminals 3 by using the positional information of the plurality of wireless terminals 3, and cluster the plurality of wireless terminals 3 in which the mutual distance between the wireless terminals 3 is equal to or less than a predetermined value", which teaches clustering reference value samples; par. 77, "The phase calculation unit 66 obtains a position centroid point of the wireless terminals 3 in the cluster from the position information of each wireless terminals 3 in the cluster", which teaches calculating a representative value based on the clustered values; par. 78, "the phase calculation unit 66 may calculate the phase of the radio wave to be reflected by each of the plurality of reflection elements 500 so that the reflection unit 50 reflects the radio waves incident from a predetermined direction toward the cluster", which teaches calculating a control pattern mapped to the representative value).
Iwabuchi discloses calculating phases targeted at cluster centroids based on user position samples, but does not explicitly utilize the specific term "codebook" to define the stored correspondence relation between the representative centroid values and the pre-calculated reflection patterns. However, Zhang and Jiang teaches (Zhang: I., "This is normally done by pre-designing a reflection beamforming codebook that can scan all the directions"; and IV., "The proposed approach first clusters users into N groups (the size of F)" and IV.A, "the users sharing similar channels are served by the same reflection vector in the codebook"; Jiang: III.A, "The proposed clustering solution is operating in two phases: 1) The first phase is clustering the channel information. The base station stores lots of the channel information, then the cloud processing unit processes the big CSI data with K-means clustering algorithm and outputs N centroids which can be regarded as the statistic channel information used to the codebook construction. It is worth noting that the sum distance from the statistic channel information to the real channel information is minimal. 2) The second phase is codebook constructing. Exploiting the centroids, the cloud processing unit constructs the codebook integrating MIMO signal processing principle."; III.C, eq 16).
It would have been obvious for one of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Iwabuchi with reflection beamforming codebook as further taught by Zhang and Jiang. The advantage of doing so is to "reduce the convergence time" and alleviate "huge beam training overhead" associated with calculating phase responses for large intelligent surfaces dynamically (Zhang: IV.B and I).
Regarding Claims 2, 5, 13 and 15, Iwabuchi as modified further teaches:
The control device according to claim 1, wherein the reference value is position information (Iwabuchi: par. 37 "estimates (measures) a position of the wireless terminal 3... and estimates the incident direction of radio waves"; and par. 77 "uses a direction from the dynamic reflector 5 to the position centroid").
Regarding Claims 3 ,6, 14 and 16, Iwabuchi as modified further teaches:
The control device according to claim 1, wherein the representative value in the codebook is generated by calculating distortion in respective clusters, which is a sum of differences between a representative value and a plurality of reference value samples, and minimizing a sum of the distortion calculated in the respective clusters (Jiang: Abstract, "The clustering centroids are used as the statistic channel information of the codebook construction which the sum distance is minimal to the real channel information"; III.A, "the sum-distance from the input data to the clustering centroids is used as the feature space of K-means clustering"; III.C, updating the centroids iteratively such that $t_{i}=arg~min_{H_{n}\in cluster:}d^{2}(H_{n},T)$ resulting in "N centroids which possess the minimal sum distance to the real channel information in the same cluster").
.Regarding Claims 4 and 10, Iwabuchi as modified further teaches:
A codebook generation device, wherein a plurality of reference value samples of a target of an IRS are clustered into a plurality of clusters, a representative value in each cluster is calculated based on reference values clustered in each cluster, a control pattern corresponding to the representative value is calculated, and a codebook is generated by calculating a correspondence relation between the representative value and the control pattern (Jiang: III.A, "The proposed clustering solution is operating in two phases: 1) The first phase is clustering the channel information. The base station stores lots of the channel information, then the cloud processing unit processes the big CSI data with K-means clustering algorithm and outputs N centroids … 2) The second phase is codebook constructing. Exploiting the centroids, the cloud processing unit constructs the codebook integrating MIMO signal processing principle."; III.C, Algorithm 1: "Input: N_t, B, Ω_H = {H_1, H_2, ..., H_L}; Output: C; First stage: Chooses N samples as the initial centroids … for a = 1 : N [Calculate the distance from point to the centroids: d(a) = ‖H_n − t_a‖²] … divide H_n into cluster_i [Update the centroid of each cluster according to the criteria: t^opt_i = min Σ_{H_n ∈ cluster_i} tr(T^H RT), i ∈ N] Until the centroids remain unchanged. The final centroids remark as: T = [t_1, t_2, ..., t_N]. Second stage: Calculate the angle information of phase(t_i) contained in t_i … non-uniform quantization codebook can be written as: C(:, i) = (1/√N_t) * e^{−j(2π/λ)d(N_T−1)cos(phase(t_i))}", where this two-phase algorithm corresponds exactly to claim 4: Phase 1 = "clustering reference value samples into clusters + calculating representative value (centroid)"; Phase 2 = "calculating control pattern (codeword c_i) corresponding to representative value (centroid t_i) + generating codebook (C) by calculating correspondence relation between representative value and control pattern."; also, Iwabuchi: par. 75-78).
Regarding Claim 11, all limitations are taught by Claims 2-3. Therefore, Claim 11 is rejected for the same reasons as Claims 2-3.
Regarding Claim 12, all limitations are taught by Claims 4 and 6. Therefore, Claim 12 is rejected for the same reasons as Claims 4 and 6.
Conclusion
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/ZHITONG CHEN/
Primary Examiner, Art Unit 2649
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