Multi-carrier transmission techniques toward flexible and efficient wireless communication systems

制度:新 ; 文部省報告番号:甲2562号 ; 学位の種類:博士(国際情報通信学) ; 授与年月日:2008/3/15 ; 早大学位記番号:新470

MIMO-OFCDM systems with joint iterative detection and optimal power allocation

This paper investigates the orthogonal frequency and code division multiplexing (OFCDM) systems with multiple input multiple output multiplexing (MIMO-OFCDM) and multicode transmission. Combining the iterative detection in the space domain and the hybrid multi-code interference (MDI) cancellation and minimum mean square error (MMSE) detection in the frequency domain, a joint iterative detection is proposed, which enables space and frequency diversity gains to be jointly exploited. Moreover, using a two-dimensional (2-D) averaging channel estimation algorithm, a close form expression is derived for the optimal power allocation between the pilot and all data channels that achieves the best system performance. It is shown that the optimal power ratio mainly depends on the channel estimation algorithm, the number of transmit antennas as well as the number of pilot and data symbols in a packet, but is not sensitive to the changes in signal-to-noise ratio (SNR) and diversity gains. Simulations are conducted to verify the derived optimal power ratio and study the performance of the proposed joint detection algorithm. It is shown that considerable improvement can be obtained when the number of loops in the joint iterative detection increases. Moreover, the system performance is enhanced significantly when the frequency domain spreading factor, N/sub F/, increases. © 2006 IEEE.published_or_final_versio

OFDM ido tsushin shisutemu ni okeru doitsu chaneru kansho jokyo hoshiki ni kansuru kenkyu

制度:新 ; 報告番号:甲3396号 ; 学位の種類:博士(国際情報通信学) ; 授与年月日:2011/9/15 ; 早大学位記番号:新571

Low-Rank Channel Estimation for Millimeter Wave and Terahertz Hybrid MIMO Systems

Massive multiple-input multiple-output (MIMO) is one of the fundamental technologies for 5G and beyond. The increased number of antenna elements at both the transmitter and the receiver translates into a large-dimension channel matrix. In addition, the power requirements for the massive MIMO systems are high, especially when fully digital transceivers are deployed. To address this challenge, hybrid analog-digital transceivers are considered a viable alternative. However, for hybrid systems, the number of observations during each channel use is reduced. The high dimensions of the channel matrix and the reduced number of observations make the channel estimation task challenging. Thus, channel estimation may require increased training overhead and higher computational complexity. The need for high data rates is increasing rapidly, forcing a shift of wireless communication towards higher frequency bands such as millimeter Wave (mmWave) and terahertz (THz). The wireless channel at these bands is comprised of only a few dominant paths. This makes the channel sparse in the angular domain and the resulting channel matrix has a low rank. This thesis aims to provide channel estimation solutions benefiting from the low rankness and sparse nature of the channel. The motivation behind this thesis is to offer a desirable trade-off between training overhead and computational complexity while providing a desirable estimate of the channel