Spatial Multidimensional Cooperative Transmission Theories And Key Technologies. Lin Bai
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Название: Spatial Multidimensional Cooperative Transmission Theories And Key Technologies

Автор: Lin Bai

Издательство: Ingram

Жанр: Зарубежная компьютерная литература

Серия:

isbn: 9789811202476

isbn:

СКАЧАТЬ Technology, Tokyo, Japan. From 2001 to 2002, he was a Special Invited Research Fellow with the Communication Research Laboratory, Tokyo. From 2006 to 2009, he was a Guest Professor with the University of Wollongong, Wollongong, NSW, Australia. He is currently a Professor with SJTU. He is a Distinguish Guest Scientist with the Commonwealth Scientific and Industrial Research Organization, Sydney, NSW, Australia. He has authored or co-authored more than 400 papers in refereed journals and conference proceedings and co-authored four books. He holds about 70 patents in antenna and wireless technologies. His current research interests include antennas, electromagnetic theory, numerical techniques of solving field problems, and wireless communication. Dr. Jin is a Fellow of IEEE, and a committee member of the Radiowave Propagation Branch and the Antenna Branch of the Chinese Institute of Electronics (CIE), Beijing, China. He was a recipient of the National Technology Innovation Award, the National Nature Science Award, the 2012 Nomination of National Excellent Doctoral Dissertation (Supervisor), the Shanghai Nature Science Award, and the Shanghai Science and Technology Progress Award.

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      Quan Yu received his Ph.D. degree in fiber optics from the University of Limoges in 1992. Since 1992, he joined the faculty of the Institute of China Electronic System Engineering Corporation. He is currently a principal research scientist at Peng Cheng Laboratory. His main areas of research interest are the architecture of wireless networks, optimization of protocols, and cognitive radios. He is an Academician of the Chinese Academy of Engineering (CAE) and the founding Editor-in-Chief of the Journal of Communications and Information Networks.

       Acknowledgments

      We would like to thank many colleagues who worked together, including Professor Jun Zhang, Professor Feng Liu, and Associate Professor Chen Chen. They gave many suggestions and helped in the completion of this book. In addition, we especially thank the students who worked hard for the preparation and proofreading of this book, including Chao Han, Shengyue Dou, Min Zhang, Yao Li, Xin Zhang, Shengsen Pan, Wenjie Bai, Yuewen Zhao, Shang Dang, Yezhen Li, and He Zhu.

      In addition, I would like to thank the National Key Research and Development Program of China (Grant No. 2017YFB0503002) and the National Natural Science Foundation of China (Grant No. 61922010).

      Finally, I am very grateful to my family for their strong support and understanding of my work.

       Lin Bai, Xianling Liang, Zhenyu Xiao, Ronghong Jin and Quan Yu

      Beijing and Shanghai

       Common Symbol Table

      1.A and a represent complex-value vectors and matrices, respectively.

      2.For matrix A, AT, AH, A−1, and A* represent its transpose, conjugate transpose, inverse of the matrix, and conjugate matrix, respectively.

      3.[A]i,j denotes the element of the ith row and the jth column of matrix A.

      4.A(a:b, c:d) represents a sub-array of matrix A whose elements are the a, . . . , b rows and c, . . . , d columns of matrix A.

      5.A(n, :) and A(:, n) represent the nth row and the nth column of the matrix A, respectively.

      6.figure and figure represent the real and the imaginary parts of complex z, respectively.

      7.||·|| represents the 2 norm of the vector or matrix and ||·|| represents the Frobenius norm of the vector or matrix.

      8.[α] represents the largest integer less than α and [α] represents the nearest integer to α.

      9.[α] represents the absolute value of α.

      10.\ represents set subtraction.

      11.In represents the n × n identity matrix.

      12.figure represents the set containing elements k(1), k(2), . . ..

      13.tr(A) represents the trace of matrix A.

      14.det(A) represents the determinant of matrix A.

      15.figure represents the length of the shortest non-zero vector in the lattice generated by matrix A.

      16.figure represents the orthogonal separating degree of matrix A with M column vectors.

      17.λ(A) and λmin(A) represent the eigenvalues of matrix A and the minimum eigenvalue of matrix A, respectively.

      18.figure represents the lattice generated by the matrix A.

      19.E[·] represents statistical expectation.

      20.〈a, b〉 represents the inner product of the vectors a and b.

      21.figure represents a complex Gaussian vector with a mean of m and a variance of C.

      22.log(·) represents the natural logarithm.

      23.0 represents a matrix with all zero elements.

      24.figure represents a set of all integers.

      25.A ⊗ B represents the Kronecker product of the matrices A and B.

       Contents

       Preface

       About the Authors

       Acknowledgments

       Common Symbol Table СКАЧАТЬ