ence plus noise, one could set the transmitted signal equal to the desired data minus the interference term; however, such an approach requires increased power and perfect knowledge of interference. It is shown in the literature that the capacity in such scenario is the same as if the interference were not present; no additional power is required to cancel the interference than is used in a nominal additive white Gaussian noise channel. Therefore, writing on dirty paper, from an infor- mation theory perspective, is equivalent to writing on clean paper when one knows in advance where the dirt is located. This concept has been used to characterize the sum-capacity and capacity region of multi-antenna multi-user channels. A dirty paper coding technique for the downlink of a MU-MIMO system uses the QR decomposition¹ of the channel matrix, as the product of a lower triangular matrix R with a unitary matrix Q such that H = QR The signal to be transmitted is precoded with the QH matrix, resulting in the effective channel R. The first user of this equivalent system sees no interference from other users, i.e., the signal may be chosen without regard for the other users. The second user sees In linear algebra, the QR decomposition of a matrix is defined as decomposition of a matrix into an orthogonal and an upper triangular matrix. The QR decomposition is often used to solve the linear least squares problem. The QR decom- position of a real square matrix A is A = QR where Q is an orthogonal matrix, i.e., QHQ = I and R is an upper triangular matrix. This can be generalized to a complex-valued square matrix A and a unitary matrix Q. If A is non-singular, then this factorization is unique if one requires the diagonal elements of R to be positive-valued. CHAPTER 10 The IEEE 802. 16m Physical Layer (Part II) interference only from the first user; this interference is known and thus may be cancelled using dirty paper coding. The other users are dealt with in a similar manner. Alternative approaches apply dirty paper techniques d