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Thesis multiuser detector decorrelator - …

The convergence behavior of turbo multiuser detection is analyzed with the help of EXIT charts.

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thesis multiuser detector decorrelatory

Implementation Issues of Multiuser Detection in CDMA Communication Systems by Gang Xu Multistage detectors have been accepted in designs for next generation CDMA base stations because they are less complex than some other multiuser detectors. In this thesis, we propose a di#erencing method to further reduce complexity. It achieves both high performance in the interference cancellation and computational e#ciency. When interference cancellation converges, the di#erence of the detection vectors between two consecutive stages is mostly zero. We recode the estimation bits, mapping from #1 to 0 and #2. Bypassing all the zero terms saves computations. Multiplication by #2 can be easily implemented in hardware as arithmetic shifts. The system delay of a #ve-stage detector will be reduced by 75# with a satisfactory bit error rate. We also investigated #xed-point implementation issues and implemented this algorithm in a real-time system using both TI's TMS320C62 DSP and ASICs. Acknowledgments Iwould like to thank Dr. Cavallaro, for his warm encouragement, valuable guidance, constant support and considerate understandings through my entire stay at Rice University. I also thank Dr. Aazhang, for his timely and accurate advice. Thanks also to Dr. Baraniuk, for serving on my committee. I also wish to thank all members in the CDMA research group, especially Chaitali and Suman, for their enlightenment on the di#erencing method. Vishwas gave me a lot of good advice and it is always my great pleasure to work with him. Sridhar and Praful contributed their time and energy in the ASIC design for the multistage detector. I greatly appreciate their e#orts and advice. I should also give many thanks to Jin and Yeli for their spiritual encouragement and help on both researchwork and ...


Chandrashekhar Thejaswi PS, Manohar S, Viswanath Ganapathy, Ranjeet Patro, and Manik Raina, “Simple Multiuser Detectors for DS-UWB Systems”, The 17th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’06), 2006.

Thesis Multiuser Detector Decorrelator - 514830 - Oh …

In this thesis, Turbo Multiuser Detection is ..

We introduce a symbol by symbol, soft-input soft-output (SISO) multiuser detector for frequency selective multiple-input multiple-output (MIMO) channels. The basic principle of this algorithm is to extract a posteriori probabilities (APPs) of all interfering symbols at each symbol interval and then feed these updated APPs as a priori probabilities (apPs) for joint APP extraction in the next symbol interval. Unlike nearoptimal block oriented sphere decoding (SD) and soft decision equalization (SDE), the computational complexity of this updating APP (UA) algorithm is linear in the number of symbols but the exponential computational load of optimal joint APP extraction makes the basic UA impractical. To decrease computations we replace the optimal joint APP extractor by a groupwise SISO multiuser detector with a soft sphere decoding core. The resulting reduced complexity updating APP (RCUA) equalizer is flexible in different situations and outperforms the traditional sub-optimal MMSE-DFE without increasing the computational costs substantially.

H. Vincent Poor and Sergio Verdu, “Probability of Error in MMSE Multiuser Detection”, IEEE Transactions on Information Theory, Vol. 43, no. 3, May 1997

An application of the chase algorithm to multiuser detection

Because of the exponential complexity of optimum multiuser detector, ..

The performance gain is determined by comparing the bit-error-rate (BER) chart of a turbo multiuser detection architecture with the BER chart of a non-turbo multiuser detector.

(2014) On Development of Some Soft Computing Based Multiuser Detection Techniques for SDMA–OFDM Wireless Communication System. PhD thesis.

In this thesis, Turbo Multiuser Detection is investigated in ..
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  • 4.3 Structure of decorrelator for V-BLAST multiuser ..

    Performance Evaluation of Multiuser Detectors with V-BLAST to MIMO Channel Mincheol Park Thesis submitted to the …

  • 4.4 Structure of two-stage detector for V-BLAST multiuser ..

    Liu, Feng (2007) An application of the chase algorithm to multiuser detection. Masters thesis, Concordia University.

  • Thesis multiuser + zf sic pic thesis mincheol park

    chart of a turbo multiuser detection architecture with the BER chart of a non-turbo multiuser detector.

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Original language: Undefined: Supervisors ..

The questions concern the performance gain that is obtained when turbo multiuser detection is used instead of non-turbo multiuser detection and the convergence behavior of turbo multiuser detection.

Language : English: Format: Thesis: ..

In this master’s thesis two types of dual-mode multiuser detectors are introduced that either dynamically switch detection mode between matched-filter and decor-relator or matched-filter and successive interference cancellation (SIC). The reason for looking into these detectors is that in some cases the difference in performance between matched-filter and decorrelator and SIC is not enough to motivate the in-crease in complexity. When the background interferences dominates compared to the multiple access interference (MAI), the decorrelator performs worse than the matched-filter, and the faster matched-filter should be used. The SIC receiver is sensitive to poor channel estimates. When the channel is rapidly varying it is harder to obtain good estimates and the SIC will suffer a severe performance degradation under these conditions. This leads to that a dual-mode design can switch to the faster matched-filter without losing much in performance. We have succeeded in creating a dual-mode detector design that reduces the overall computational requirement while maintaining similar performance as that

A Channel-Shortening Multiuser Detector for - …

Space Division Multiple Access(SDMA) based technique as a subclass of Multiple Input Multiple Output (MIMO) systems achieves high spectral efficiency through bandwidth reuse
by multiple users. On the other hand, Orthogonal Frequency Division Multiplexing (OFDM) mitigates the impairments of the propagation channel. The combination of SDMA and
OFDM has emerged as a most competitive technology for future wireless communication system. In the SDMA uplink, multiple users communicate simultaneously with a multiple
antenna Base Station (BS) sharing the same frequency band by exploring their unique user specific-special spatial signature. Different Multiuser Detection (MUD) schemes have been proposed at the BS receiver to identify users correctly by mitigating the multiuser
interference. However, most of the classical MUDs fail to separate the users signals in the over load scenario, where the number of users exceed the number of receiving antennas. On the other hand, due to exhaustive search mechanism, the optimal Maximum Likelihood (ML)
detector is limited by high computational complexity, which increases exponentially with increasing number of simultaneous users. Hence, cost function minimization based Minimum Error Rate (MER) detectors are preferred, which basically minimize the probability of error by iteratively updating receiver’s weights using adaptive algorithms such as Steepest Descent (SD), Conjugate Gradient (CG) etc. The first part of research proposes Optimization Techniques (OTs) aided MER detectors to overcome the shortfalls of the CG based MER detectors. Popular metaheuristic
search algorithms like Adaptive Genetic Algorithm (AGA), Adaptive Differential Evolution Algorithm (ADEA) and Invasive Weed Optimization (IWO), which rely on an intelligent search of a large but finite solution space using statistical methods, have been applied for
finding the optimal weight vectors for MER MUD. Further, it is observed in an overload SDMA–OFDM system that the channel output phasor constellation often becomes linearly
non-separable. With increasing the number of users, the receiver weight optimization task turns out to be more difficult due to the exponentially increased number of dimensions of the weight matrix. As a result, MUD becomes a challenging multidimensional optimization problem. Therefore, signal classification requires a nonlinear solution. Considering this, the second part of research work suggests Artificial Neural Network (ANN) based MUDs on thestandard Multilayer Perceptron (MLP) and Radial Basis Function (RBF) frameworks for

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