Iterative Training Sequence Design for Multiuser MIMO Systems
Fung, Carrson C.
|關鍵字:||序列設計;多使用者;多輸入多輸出;training sequence desgin;multiuser;MIMO|
Next generation communication standards are set to use MIMO transmission techniques to improve capacity and link reliability. This methods, which include SU-MIMO, MUMIMO, and network MIMO (also known as CoMP), are expected to work seamlessly with OFDM and OFDMA to provide ease of decoding and multiple access. The reduced decoding complexity, however, is traded off by requiring accurate channel information, and synchronization (e.g. frame and carrier frequency offset). Unfortunately, proposed preambles and pilots, or training sequences, in these standards are not necessarily designed to render optimal channel estimation performance; rather, they are usually biased toward providing accurate frame synchronization. The optimality is destroyed because these sequences do not account and exploit physical channel attributes, such as transmitter-receiver coupling and spatial correlation, which can dramatically improve estimation accuracy if they are properly utilized during the design process. The sequence design problem for multiple user systems is exacerbated by the existence of colored noise, which can make the overall design problem nonconvex. Thus, finding the global optimal solution becomes computational expensive. Previous works have bypassed this problem by assuming little or no spatial coupling exists between the transmitter and receiver, such that the MIMO channel can be sufficiently modeled using the Kronecker model. This assumption, however, is questionable in most actual scenarios. Further extension has been made by using nonlinear optimization method to refine the solution obtained using the above technique. This, of course, does not guarantee that the global optimal solution can be obtained. In this thesis, an overview of SU-MIMO transmission techniques will be given, followed by a general discussion on sequence design techniques and MIMO channel estimation for single- and multiuser systems. Next, an iterative training sequence design scheme called iterative superimposed training sequence design with multiple interferers, or ISIMI, is presented for estimating MIMO channels with colored noise. The proposed approach does not utilized nonlinear optimization as used in previous literature, nor make any assumption about the lack of interdependence between the transmitter and receiver. The approach is proven to converge to at least a local optimal solution and is shown consistently by Monte Carlo simulation to outperform previously proposed MSE based approach for 2×2 and 4×4 MIMO systems, respectively, in terms of MSE. Analytical results illustrating efficacy and deficiency of ISIMI is also included. In addition, computational complexity of ISIMI is illustrated in terms of number of arithmetic operations. The thesis is concluded with a discussion possible modification for ISIMI in order to further improve its performance. This is followed by a discussion on how it can be extended to robust training sequence design for MIMO system with multiple interferers, and sequence design with limited feedback.