Multiuser Detection in Asynchronous Multibeam Communications

Chaouech, Helmi

doi:10.5121/ijwmn.2012.4102

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…However, there is a need to establish a balance between improved signals and noise reduction systems such that the cost of detection and risk of missing the target will be carried out at a minimum possible cost. These include detection-interpolation scheme [13], penalty function technique [14], minimax noise variance estimation [15], performance improved nonlinear detector of spread spectrum receiver [16], nonparametric dynamic model for monitoring changes in signal detection performance [17], synthetic antenna array concept for signal detection enhancement [18], algorithm based on sparsity hypotheses [19], successive interference cancellation architecture and channel decoding to treat the co-channel interference [20], Dynamic Spectrum Access (DSA,) [21], and orthogonal frequency division multiplexing scheme for fading/interference mitigation [7,8]. Apart from Broumandan [18] that carried out research on enhancement of signal detection using synthetic antenna array concept, scanty studies were identified in applying the component-based circuitry for the enhancement of signal detection.…”

Section: Introductionmentioning

confidence: 99%

Detection under Noise Using Component Improvement Strategy

Ogunti¹,

Lawal²,

Olatunji³

et al. 2015

ujeee

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Inaccuracy in signal detection due to presence of noise in signal is responsible for fading/interference, this noise needs to be reduced for optimal signal detection, and detection must be accurate enough to minimize the risk of false alarm. A noise reduction model was developed to improve signal detection using component improvement strategy. The system was implemented on MATLAB software package. It can be seen from the results that for a given probability of false alarm (P FA ), the detection performance increases monotonically with the ENR based on the balanced probability of not meeting target of 0.5. It can be generally concluded from the results of the study that signal detection could be fully enhanced with the application of six sigma component-based improvement system. This is an indication that component-based sigma improvement system played a significant role in signal detection performance.

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Section: Introductionmentioning

confidence: 99%

Detection under Noise Using Component Improvement Strategy

Ogunti¹,

Lawal²,

Olatunji³

et al. 2015

ujeee

View full text Add to dashboard Cite

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Generalized Receiver with Parallel Interference Cancellation for Multiuser Detection

Tuzlukov

2021

Wseas Transactions on Systems and Control

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Parallel interference cancellation is considered as a simple yet effective multiuser detector for direct -sequence code-division multiple-access (DS-CDMA) systems. However, system performance be deteriorated due to unreliable interference cancellation in the early stages. Thus, a detector with the partial parallel interfere-nce cancellation in which the partial cancellation factors are introduced to control the interference cancellation level has been developed as a remedy. Although the partial cancellation factors are crucial, complete solutions for their optimal values are not available. In this paper, we consider a two-stage decoupled generalized receiver with the partial parallel interference cancellation. Using the minimum bit error rate (BER) criterion, we derive a complete set of optimal partial cancellation factors. This includes the optimal partial cancellation factors for pe-riodic and aperiodic spreading codes in channels with the additive white Gaussian noise and multipath chann-els. Simulation results demonstrate that the considered theoretical optimal partial cancellation factors agree clo-sely with empirical ones. The proposed two-stage generalized receiver with the partial parallel interference can-cellation using the derived optimal partial cancellation factors outperforms not only a two-stage, but also a three-stage conventional generalized receiver with the full parallel interference cancellation.

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Multiuser Detection in Asynchronous Multibeam Communications

Abstract: ABSTRACT

Cited by 2 publications

References 26 publications

Detection under Noise Using Component Improvement Strategy

Detection under Noise Using Component Improvement Strategy

Generalized Receiver with Parallel Interference Cancellation for Multiuser Detection

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