Additional Control Logic
5.3 The Performances of the Proposed Channel Estimation Methods
In this section, the performances of the proposed channel estimation methods are evaluated by computer simulations. In the following simulations, EISI “Vehicular A”
is considered. The 16 pilot subcarriers are equispaced along frequency direction, i.e.
the indices of the pilot subcarriers are {0, 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60} within 64 subcarriers. An all-pilot preamble is attached in front of the data symbols. It is assumed that the maximum path delay time is known at the receiver and that synchronization is perfect.
0 5 10 15 20 25 30 35 40 45
Figure 5.12 ANMSE performances of the channel estimation methods in the “Ve-hicular A” channel with fnd =0.040
Figure 5.13 ANMSE performances of the channel estimation methods in the “Ve-hicular A” channel with fnd =0.083
0 5 10 15 20 25 30 35 40 45 BER Yeh's ICI reduction 3rd
ICI cancellation 3rd, Ideal CSI ICI-free
Figure 5.14 BER performances of the channel estimation methods combined with data detection methods in the “Vehicular A” channel with fnd =0.040
0 5 10 15 20 25 30 35 40 45 BER Yeh's ICI reduction 3rd
ICI cancellation 3rd, Ideal CSI ICI-free
Figure 5.15 BER performances of the channel estimation methods combined with data detection methods in the “Vehicular A” channel with fnd =0.083
In Figure 5.12 and Figure 5.13, the terms “Chen’s LS, preamble” and “Chen’s LS, pilot” indicate that Chen’s method of LS channel estimation, introduced in Section 3.2.3, are applied to the all-pilot preamble and the pilot subcarriers, respectively. The term “Yeh’s ICI reduction, pilot” indicates that Yeh’s algorithm of ICI reduction method [11] with 3 detection iterations, introduced in Section 3.2.4, is applied to the pilot subcarriers. The term “Modified ICI reduction” indicates the proposed modifica-tion of Yeh’s ICI-reducmodifica-tion method with 3 detecmodifica-tion iteramodifica-tions, introduced in Secmodifica-tion 4.2.1. The term “Hybrid LS/ICI reduction” indicates the proposed hybrid LS/ICI-reduction channel estimation method, introduced in Section 4.2.2.
In Figure 5.14 and Figure 5.15, the term “ICI-free” indicates the theoretical BER performance of the coherent detection in the time-invariant flat Rayleigh fading channel for the reference of the ICI-free case. The ordinal number appended to “ICI cancellation” and “Yeh’s ICI reduction” indicates the number of the iterations per-formed in the two methods. The terms “FSDMMSE” and “Choi’s SDMMSE” indicate that the proposed frequency-domain successive detection method with MMSE tion (see Section 4.1) and Choi’s method of successive detection with MMSE detec-tion [7] are adopted in data detecdetec-tion, respectively. The term “Ideal CSI” indicates that ideal channel state information is applied to data detection.
Figure 5.12 and Figure 5.13 illustrate ANMSE performances of the channel esti-mation methods in the “Vehicular A” channel with fnd =0.040, and fnd =0.083, respectively. The channel estimation error of the proposed modification of Yeh’s ICI-reduction method with 3 detection iterations is less than that of Yeh’s ICI-reduction method when fnd =0.083. However, this benefit is only obtained in high SNR case. This is because the estimated slope of the channel tap, αˆli, obtained by hˆ ( )avei l and hˆ (i−1 N−1, )l in Figure 4.2 suffer from more noise effect than that
obtained by hˆ ( )avei l and hˆ ( )avei−1 l in Figure 3.6. In other words, it means that the
vari-ance of the estimated slope of the channel tap, αˆli, is large when the distance between the two reference points with noise is small. It will induce large estimation error. Be-sides, since ICI terms can not be cancelled perfectly in the ICI cancellation procedure of Yeh’s method, the channel estimation error increase as fnd becomes large.
Figure 5.14 and Figure 5.15 illustrate the BER performances of the channel esti-mation methods combined with data detection methods in the “Vehicular A” channel with fnd =0.040, and fnd =0.083, respectively. The proposed hybrid LS/ICI-reduc-tion channel estimaLS/ICI-reduc-tion method has the best performance of all. The performance loss of the proposed modification of Yeh’s ICI reduction method is about 1~3dB in the SNR range from 10 dB to 30 dB when comparing to the proposed hybrid LS/ICI-re-duction channel estimation method. Although the two proposed methods outperform Yeh’s ICI-reduction method and ICI cancellation method with 3 detection iterations, they still suffer severe ICI effect. There is still large performance loss compared to the proposed frequency-domain successive detection method with ideal channel state in-formation.
By comparison of the simulation results in the previous section (see Figure 5.11), the normalized mean square error η of the channel estimation must be less than 0.02%, i.e. ANMSE must be less than -37dB, for utilizing the time diversity effec-tively for the proposed data detection methods with q = 8 when fnd =0.083 and SNR = 35dB. However, Figure 5.13 shows that the two proposed channel estimation methods do not satisfy the preciseness requirements of the proposed data detection methods.
Chapter 6 Conclusion
In this thesis, efficient frequency-domain successive detection methods for OFDM systems in fast fading channels are proposed. By evaluating the proposed methods in terms of computational complexities and BER performances, it shows that they oper-ate well in the targeted channel environments and their computational complexities are much less than those of the conventional successive detection. However, their computational complexities them are still larger than those of the ICI cancellation methods. Thus, it is a challenging task to find out an adaptive strategy to switch be-tween the low-complexity methods and the proposed methods dynamically according to transmission environments, or to lower the computational complexities of the pro-posed methods.
Unfortunately, the tolerated channel estimation error of the proposed detection methods is very small according to the simulation results. Thus, existing common channel estimation methods are not good enough for the proposed detection methods.
To make the coherent detection feasible, some channel estimation methods are pro-posed. The simulation results show that the proposed channel estimation methods out-perform the existing common channel estimation methods but do not satisfy the pre-ciseness requirements of the proposed detection methods. Thus, it is still a quite chal-lenging task for future research.
Multiple input multiple output (MIMO) techniques [15] [26] are widely adopted in the next generation communication systems. Thus, data detection and channel es-timation for MIMO-OFDM systems in fast fading channels is an original research topic. In these systems, not only ICI but also inter-antenna interference (IAI) will be induced. The main goal is to find out an efficient strategy to suppress the interference and extract the desired signal. With belief, the concepts of the proposed methods can also be applied to these systems.
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Autobiography
蔡金融，1982 年 2 月 6 日出生於台北市。2004 年自國立交通大學電 信工程學系畢業，隨即進入國立交通大學電子工程研究所攻讀碩士學 位，致力於訊號處理與通訊系統研究。論文題目是正交分頻多工通信 系統於時變與多重路徑衰減通道之通道估測與訊號偵測設計。