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Hsuan-Jung Su

Publications and source records attributed to Hsuan-Jung Su.

22 records · Page 2Linked to original sources

Prediction-based Adaptation (PRADA) Algorithm for Modulation and Coding

In this paper, we propose a novel adaptive modulation and coding (AMC) algorithm dedicated to reduce the feedback frequency of the channel state information (CSI). There have been already plenty of works on AMC so as to exploit the bandwidth more efficiently with the CSI feedback to the transmitter. However, in some occasions, frequent CSI feedback is not favorable in these systems. This work considers finite-state Markov chain (FSMC) based channel prediction to alleviate the feedback while maximizing the overall throughput. We derive the close-form of the frame error rate (FER) based on channel prediction using limited CSI feedback. In addition, instead of switching settings according to the CSI, we also provide means to combine both CSI and FER as the switching parameter. Numerical results illustrate that the average throughput of the proposed algorithm has significant performance improvement over fixed modulation and coding while the CSI feedback being largely reduced.

cs.IT↗

Peak to Average Power Ratio Reduction for Space-Time Codes That Achieve Diversity-Multiplexing Gain Tradeoff

Zheng and Tse have shown that over a quasi-static channel, there exists a fundamental tradeoff, known as the diversity-multiplexing gain (D-MG) tradeoff. In a realistic system, to avoid inefficiently operating the power amplifier, one should consider the situation where constraints are imposed on the peak to average power ratio (PAPR) of the transmitted signal. In this paper, the D-MG tradeoff of multi-antenna systems with PAPR constraints is analyzed. For Rayleigh fading channels, we show that the D-MG tradeoff remains unchanged with any PAPR constraints larger than one. This result implies that, instead of designing codes on a case-by-case basis, as done by most existing works, there possibly exist general methodologies for designing space-time codes with low PAPR that achieve the optimal D-MG tradeoff. As an example of such methodologies, we propose a PAPR reduction method based on constellation shaping that can be applied to existing optimal space-time codes without affecting their optimality in the D-MG tradeoff. Unlike most PAPR reduction methods, the proposed method does not introduce redundancy or require side information being transmitted to the decoder. Two realizations of the proposed method are considered. The first is similar to the method proposed by Kwok except that we employ the Hermite Normal Form (HNF) decomposition instead of the Smith Normal Form (SNF) to reduce complexity. The second takes the idea of integer reversible mapping which avoids the difficulty in matrix decomposition when the number of antennas becomes large. Sphere decoding is performed to verify that the proposed PAPR reduction method does not affect the performance of optimal space-time codes.

cs.IT↗

Cognitive Radio with Partial Channel State Information at the Transmitter

In this paper, we present the cognitive radio system design with partial channel state information known at the transmitter (CSIT).We replace the dirty paper coding (DPC) used in the cognitive radio with full CSIT by the linear assignment Gel'fand-Pinsker coding (LA-GPC), which can utilize the limited knowledge of the channel more efficiently. Based on the achievable rate derived from the LA-GPC, two optimization problems under the fast and slow fading channels are formulated. We derive semianalytical solutions to find the relaying ratios and precoding coefficients. The critical observation is that the complex rate functions in these problems are closely related to ratios of quadratic form. Simulation results show that the proposed semi-analytical solutions perform close to the optimal solutions found by brute-force search, and outperform the systems based on naive DPC. Asymptotic analysis also shows that these solutions converge to the optimal ones solved with full CSIT when the K-factor of Rician channel approaches infinity. Moreover, a new coding scheme is proposed to implement the LA-GPC in practice. Simulation results show that the proposed practical coding scheme can efficiently reach the theoretical rate performance.

cs.IT↗

Filter and nested-lattice code design for fading MIMO channels with side-information

Linear-assignment Gel'fand-Pinsker coding (LA-GPC) is a coding technique for channels with interference known only at the transmitter, where the known interference is treated as side-information (SI). As a special case of LA-GPC, dirty paper coding has been shown to be able to achieve the optimal interference-free rate for interference channels with perfect channel state information at the transmitter (CSIT). In the cases where only the channel distribution information at the transmitter (CDIT) is available, LA-GPC also has good (sometimes optimal) performance in a variety of fast and slow fading SI channels. In this paper, we design the filters in nested-lattice based coding to make it achieve the same rate performance as LA-GPC in multiple-input multiple-output (MIMO) channels. Compared with the random Gaussian codebooks used in previous works, our resultant coding schemes have an algebraic structure and can be implemented in practical systems. A simulation in a slow-fading channel is also provided, and near interference-free error performance is obtained. The proposed coding schemes can serve as the fundamental building blocks to achieve the promised rate performance of MIMO Gaussian broadcast channels with CDIT or perfect CSIT

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