227 research outputs found

    MMSE multiuser detection for array multicarrier DS-CDMA in fading channels

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    THE performance and robust implementation of a blind CMOE receiver for MC-CDMA systems

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    This paper studies a new robust constrained minimum output energy (CMOE)-based blind detector for multicarrier code division multiple access (MC-CDMA) systems. The proposed receiver intends to minimize the receiver's output energy while preserving the components of the desired user. By imposing quadratic weight constraints, the CMOE detector is made more robust against signal modeling errors, and a better performance over the standard CMOE detector is obtained. Steady-state signal-to-interference-plus-noise ratio (SINR) analysis of the blind CMOE detector and the minimum mean-squared error (MMSE) method with training sequences is presented. Numerical results show that the performance of the new robust detector is comparable to subspace-based method using exact singular value decomposition (SVD).published_or_final_versio

    A Linear Multi-User Detector for STBC MC-CDMA Systems based on the Adaptive Implementation of the Minimum-Conditional Bit-Error-Rate Criterion and on Genetic Algorithm-assisted MMSE Channel Estimation

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    The implementation of efficient baseband receivers characterized by affordable computational load is a crucial point in the development of transmission systems exploiting diversity in different domains. In this paper, we are proposing a linear multi-user detector for MIMO MC-CDMA systems with Alamouti’s Space-Time Block Coding, inspired by the concept of Minimum Conditional Bit-Error-Rate (MCBER) and relying on Genetic-Algorithm (GA)-assisted MMSE channel estimation. The MCBER combiner has been implemented in adaptive way by using Least-Mean-Square (LMS) optimization. Firstly, we shall analyze the proposed adaptive MCBER MUD receiver with ideal knowledge of Channel Status Information (CSI). Afterwards, we shall consider the complete receiver structure, encompassing also the non-ideal GA-assisted channel estimation. Simulation results evidenced that the proposed MCBER receiver always outperforms state-of-the-art receiver schemes based on EGC and MMSE criterion exploiting the same degree of channel knowledge (i.e. ideal or estimated CSI)

    Channel identifiability of OFDM-CDMA system based on subspace method

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    Subspace method is well-known in CDMA channel estimation. But a basic problem, channel identifiability by subspace method, is still not well-solved. In this paper, two subspace based blind methods for estimating the channel responses of a OFDM-CDMA system in downlink and uplink are discussed respectively. Under some reasonable assumptions, it is mathematically proved that subspace method for downlink can estimate the channel subject to a scalar ambiguity, and the method for uplink can give the channel responses subject to a diagonal matrix ambiguity. The methods do not need precise channel order information (only an upper bound for the orders is required). Simulations show that the methods are effective and robust.published_or_final_versio

    Cyclic Prefix-Free MC-CDMA Arrayed MIMO Communication Systems

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    The objective of this thesis is to investigate MC-CDMA MIMO systems where the antenna array geometry is taken into consideration. In most MC-CDMA systems, cyclic pre xes, which reduce the spectral e¢ ciency, are used. In order to improve the spectral efficiency, this research study is focused on cyclic pre x- free MC-CDMA MIMO architectures. Initially, space-time wireless channel models are developed by considering the spatio-temporal mechanisms of the radio channel, such as multipath propaga- tion. The spatio-temporal channel models are based on the concept of the array manifold vector, which enables the parametric modelling of the channel. The array manifold vector is extended to the multi-carrier space-time array (MC-STAR) manifold matrix which enables the use of spatio-temporal signal processing techniques. Based on the modelling, a new cyclic pre x-free MC- CDMA arrayed MIMO communication system is proposed and its performance is compared with a representative existing system. Furthermore, a MUSIC-type algorithm is then developed for the estimation of the channel parameters of the received signal. This proposed cyclic pre x-free MC-CDMA arrayed MIMO system is then extended to consider the effects of spatial diffusion in the wireless channel. Spatial diffusion is an important channel impairment which is often ignored and the failure to consider such effects leads to less than satisfactory performance. A subspace-based approach is proposed for the estimation of the channel parameters and spatial spread and reception of the desired signal. Finally, the problem of joint optimization of the transmit and receive beam- forming weights in the downlink of a cyclic pre x-free MC-CDMA arrayed MIMO communication system is investigated. A subcarrier-cooperative approach is used for the transmit beamforming so that there is greater flexibility in the allocation of channel symbols. The resulting optimization problem, with a per-antenna transmit power constraint, is solved by the Lagrange multiplier method and an iterative algorithm is proposed

    Widely Linear vs. Conventional Subspace-Based Estimation of SIMO Flat-Fading Channels: Mean-Squared Error Analysis

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    We analyze the mean-squared error (MSE) performance of widely linear (WL) and conventional subspace-based channel estimation for single-input multiple-output (SIMO) flat-fading channels employing binary phase-shift-keying (BPSK) modulation when the covariance matrix is estimated using a finite number of samples. The conventional estimator suffers from a phase ambiguity that reduces to a sign ambiguity for the WL estimator. We derive closed-form expressions for the MSE of the two estimators under four different ambiguity resolution scenarios. The first scenario is optimal resolution, which minimizes the Euclidean distance between the channel estimate and the actual channel. The second scenario assumes that a randomly chosen coefficient of the actual channel is known and the third assumes that the one with the largest magnitude is known. The fourth scenario is the more realistic case where pilot symbols are used to resolve the ambiguities. Our work demonstrates that there is a strong relationship between the accuracy of ambiguity resolution and the relative performance of WL and conventional subspace-based estimators, and shows that the less information available about the actual channel for ambiguity resolution, or the lower the accuracy of this information, the higher the performance gap in favor of the WL estimator.Comment: 20 pages, 7 figure
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