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Title: Single and Multicarrier Adaptive Transmission Systems with Long-Range Prediction Aided by Noise Reduction
Authors: Jia, Tao
Advisors: Huaiyu Dai, Committee Member
Brian L. Hughes, Committee Member
Hans Hallen, Committee Co-Chair
Alexandra Duel-Hallen, Committee Chair
Keywords: noise reduction
multicarrier transmission
long-range fading prediction
adaptive modulation
Issue Date: 14-Nov-2008
Degree: PhD
Discipline: Electrical Engineering
Abstract: Adaptive transmission methods have evolved as one of the key enabling technologies to meet the increasing demand for high-speed wireless data access services. In this dissertation, we address several adaptive transmission systems and techniques required for their implementation. First, we focus on multicarrier code-division multiple access (MC-CDMA) system with adaptive frequency hopping (AFH). A suboptimal water-filling (WF) channel allocation algorithm was previously proposed for the reverse link of this system. To overcome the limitations of the WF algorithm in the presence of fading-induced near-far problem, a new allocation algorithm is proposed and demonstrated to improve performance when the conventional matched filter (MF) receiver is employed. Moreover, the allocation methods are extended to accommodate multiuser detectors (MUDs) at the receiver for MC-CDMA system with AFH. It is demonstrated that the combination of the improved allocation algorithm and the linear MUDs is very efficient in mitigating fading and multi-access interference (MAI) for realistic mobile radio channels with correlated subcarriers, channel state information (CSI) mismatch, and imperfect power control. Numerical results show that the proposed adaptive transmission method has much greater system capacity than conventional non-adaptive MC direct-sequence (DS)-CDMA system. Second, the adaptive modulation (AM) system is investigated. To ensure high spectral efficiency (SE) for AM systems, the CSI needs to be predicted to compensate for the feedback and data processing delay and system constraints. The long-range prediction (LRP) method achieves high prediction accuracy at practical predication ranges when the signal-to-noise ratio (SNR) of the observations is sufficiently high. However, its accuracy degrades severely at low and medium SNR. Hence, the noise reduction (NR) techniques are required for the LRP to achieve the desired prediction accuracy. A novel data-aided noise reduction (DANR) method is proposed. The DANR includes an adaptive pilot transmission mechanism, robust noise reduction, and decision-directed channel estimation. Due to improved prediction accuracy and low pilot rates, the DANR results in higher SE than previously proposed NR techniques, which rely on oversampled pilots. While adaptive coded modulation (ACM) is more sensitive to prediction errors than uncoded adaptive modulation (UAM), this DANR method maintains the coding gain and outperforms previous investigated prediction methods in terms of SE at practical prediction ranges. It is also demonstrated that adaptive modulation aided by LRP has better performance for the realistic physical model than for the Jakes model in the practical SNR range. Finally, we investigate the orthogonal frequency division-multiplex (OFDM) system with adaptive bit-interleaved coded modulation (ABICM) aided by LRP. New ABICM methods based on the expurgate bound are proposed. They achieve better bit-error rate (BER) accuracy than the existing method. In particular, one of the proposed methods generates the BER that is very close to the specified target BER. Compared with ACM and UAM, the ABICM is much less sensitive to prediction errors. However, the LRP technique still significantly improves the SE of ABICM over the outdated CSI method at practical prediction ranges. In summary, we address several important problems in the implementation of single and multicarrier adaptive transceivers. In particular, we design an improved allocation algorithm to efficiently exploit the predicted CSI in the MC-CDMA system with AFH. Combined with MUDs, this system achieves higher system capacity than the non-adaptive MC-CDMA systems. Next, a DANR technique is proposed for single-carrier adaptive modulation system. Due to improved prediction accuracy and low pilot rates, the DANR results in higher SE than previously proposed NR techniques, which rely on oversampled pilots. Finally, we investigate ABICM, which is less sensitive to the prediction errors than UAM and ATCM. New adaptation methods that achieve improved BER accuracy are proposed for ABICM. It is demonstrated that with the aid of LRP, the OFDM system with ABICM maintains high SE at long prediction ranges.
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