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In this paper, we consider the uplink transmission of a system with one multi-antenna base station (BS) and multiple single antenna user equipments (UEs), which forms a virtual multiple-input multiple-output (MIMO) system. To investigate the capacity maximization problem under per-antenna power constraints, the alternating direction method of multipliers (ADMM) is exploited to obtain the optimal solution...
Block diagonalization (BD) is a well-known linear precoding scheme for multi-user multiple-input multiple-output (MU-MIMO) downlink transmission. BD precoding achieves good performance but results in high computational complexity overheads due to two singular value decomposition (SVD) operations for each user. By replacing the first SVD operation with a less complex solution, the QR decomposition...
Implementation-efficient nonlinear mitigation algorithms for digital coherent transceivers are introduced. Q-improvement by different algorithm combinations is presented for different transmission scenarios. Expectations on further improvement thorough noise reshaping and cycle slip reduction are also addressed.
Image segmentation is very essential and critical to image processing and pattern recognition. It is known that, color image segmentation approaches are based on monochrome segmentation approaches operating in different color spaces. So in this paper, an improved method which uses the FSVM (fuzzy support vector machines) algorithm for color image segmentation in the HSI (hue-saturation-intensity)...
The partial transmit sequence (PTS) is a very promising algorithm for reducing peak-to-average ratio (PAPR) in OFDM system. However, the high average computational time complexity of rotation phase coefficient searching in PTS algorithm makes it difficult to implement. For reducing the average computational time complexity of PTS algorithm with negligible performance penalty, we proposed a dynamic...
In this paper, a new algorithm for signal detection, namely partial grouping maximization likelihood algorithm, is proposed to achieve satisfactory performance with moderate computational complexity. The new algorithm is bawd on maximization likelihood principle and the idea of grouping, and the performance assessment shows that it is superior to the linear detector and ordinary grouping algorithm,...
In this paper, an improved fuzzy membership function determination is proposed to train the fuzzy support vector machine (FSVM) for classification which the sample set in reality environment is increasing, and it often contains a lot of noise and outliers. In the improved algorithm, the sample points have the different types of memberships in different regions. The dual membership is introduced to...
We focus on the maximization-likelihood algorithms and its application aimed at achieving satisfactory performance at the price of a moderate computational complexity. We propose a new algorithm named step-down grouping maximization likelihood (SGML). At the analysis stage, some interesting properties shared by the proposed procedures are proven. Finally, the performance assessment shows that the...
Turbo decoder estimates message values sent from transmitter by computing iteratively to get the maximum posteriori probability. It will be inefficient if the number of iteration is set irrationally. To reduce decoding process latency, lots of stopping criteria for turbo decoding were proposed. Those methods also increase computation complexity at each iteration. The computation complexity may become...
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