357 research outputs found

    Multiuser Detection with Decision-Feedback Detectors and PIC in MC-CDMA System

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    In this paper we propose an iterative parallel decision feedback (P-DF) receivers associated with parallel interference cancellation (PIC) for multicarrier code division multiple access (MC-CDMA) systems in a Rayleigh fading channel (cost 207). First the most widely detection techniques, minimum mean-squared error MMSE, Maximum Likelihood ML and PIC were investigated in order to compare their performances in terms of Bit Error Rate (BER) with parallel feedback detection P-DFD. A MMSE DF detector that employs parallel decision-feedback (MMSE-P-DFD) is considered and shows almost the same BER performance with MMSE and ML, which present a better result than the other techniques. In a second time, an iterative proposed method based on the multi-stage techniques P-DFD (parallel DFD with two stages) and PIC was exploited to improve the performance of the system

    Multiuser MIMO-OFDM for Next-Generation Wireless Systems

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    This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

    Multi-user receiver structures for direct sequence code division multiple access

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    Correcting the Bias of Subtractive Interference Cancellation in CDMA: Advanced Mean Field Theory

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    In this paper we introduce an advanced mean field method to correct the inherent bias of conventional subtractive interference cancellation in Code Division Multiple Access (CDMA). In simulations, we get a performance quite close to that of the individual optimal exponential complexity detector and significant improvements over current state-of-the-art subtractive interference cancellation in all setups tested, for example in one case doubling the number of user at a bit error rate of. To obtain such a good performance for finite size systems, where the performance is normally degraded by the presence of suboptimal fix-point solutions, it is crucial to use the method in conjunction with mean field annealing, i.e. solving the fixed point equations at decreasing temperatures (noise levels). In the limit of infinite large system size, the new subtractive interference cancellation scheme is expected to be identical to the individual optimal detector. The computational complexity is cubic in the number of users whereas conventional (naive mean field) subtractive interference cancellation is quadratic. We also present a quadratic complexity approximation to our new method that also gives performance improvements, but in addition requires knowledge of the spreading code statistics. The proposed methodology is quite general and is expected to be applicable to other digital communication problems

    A genetic algorithm-assisted semi-adaptive MMSE multi-user detection for MC-CDMA mobile communication systems

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    In this work, a novel Minimum-Mean Squared-Error (MMSE) multi-user detector is proposed for MC-CDMA transmission systems working over mobile radio channels characterized by time-varying multipath fading. The proposed MUD algorithm is based on a Genetic Algorithm (GA)-assisted per-carrier MMSE criterion. The GA block works in two successive steps: a training-aided step aimed at computing the optimal receiver weights using a very short training sequence, and a decision-directed step aimed at dynamically updating the weights vector during a channel coherence period. Numerical results evidenced BER performances almost coincident with ones yielded by ideal MMSE-MUD based on the perfect knowledge of channel impulse response. The proposed GA-assisted MMSE-MUD clearly outperforms state-of-the-art adaptive MMSE receivers based on deterministic gradient algorithms, especially for high number of transmitting users
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