| 1. |
- Duong, Quang Trung, et al.
(författare)
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On The Symbol Error Probability of Distributed-Alamouti Scheme
- 2009
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Ingår i: Journal of Communications. - : Academy Publisher. - 1796-2021 .- 2374-4367. ; 4:7, s. 437-444
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Tidskriftsartikel (refereegranskat)abstract
- Taking into account the relay’s location, we analyze the maximum likelihood (ML) decoding performance ofdualhop relay network, in which two amplify-and-forward (AF) relays employ the Alamouti code in a distributed fashion. In particular, using the well-known moment generating function (MGF) approach we derive the closed-form expressions of the average symbol error probability (SEP) for M-ary phase-shift keying (M-PSK) when the relays are located nearby either the source or destination. The analytical result is obtained as a single integral with finite limits and the integrand composed solely of trigonometric functions. Assessing the asymptotic characteristic of SEP formulas in the high signal-to-noise ratio regime, we show that the distributed-Alamouti protocol achieves a full diversity order. We also perform the Monte-Carlo simulations to validate our analysis. In addition, based on the upper bound of SEP we propose an optimal power allocation between the first-hop (the source-to-relay link) and second-hop (the relay-to-destination link) transmission. We further show that as the two relays are located nearby the destination most of the total power should be allocated to the broadcasting phase (the first-hop transmission). When the two relays are placed close to the source, we propose an optimal transmission scheme which is a non-realtime processing, hence, can be applied for practical applications. It is shown that the optimal power allocation scheme outperforms the equal power scheme with a SEP performance improvement by 2-3 dB.
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| 2. |
- Duong, Quang Trung, et al.
(författare)
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Performance analysis of cooperative spatial multiplexing networks with AF/DF relaying and linear receiver over Rayleigh fading channels
- 2015
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Ingår i: Wireless Communications & Mobile Computing. - : Elsevier. - 1530-8669 .- 1530-8677. ; 15:3, s. 500-509
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Tidskriftsartikel (refereegranskat)abstract
- Cooperative spatial multiplexing (CSM) system has played an important role in wireless networks by offering a substantial improvement in multiplexing gain compared with its cooperative diversity counterpart. However, there is a limited number of research works that consider the performance of CSM systems. As such, in this paper, we have derived exact performance of CSM with amplify-and-forward and decode-and-forward relays in terms of outage capacity and ergodic capacity. We have shown that CSM systems yield a unity diversity order regardless of the number of antennas at the destination and the number of relays in the networks, which is the direct result of diversity and multiplexing gain trade-off. Our analytical expressions are corroborated by Monte-Carlo simulations.
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| 3. |
- Duong, Quang Trung, et al.
(författare)
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Symbol Error Probability of Distributed-Alamouti Scheme in Wireless Relay Networks
- 2008
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Konferensbidrag (refereegranskat)abstract
- In this paper, we analyze the maximum likelihood decoding performance of non-regenerative cooperation employing Alamouti scheme. Specifically, we derive two closed-form expressions for average symbol error probability (SEP) when the relays are located near by the source or destination. The analytical results are obtained as a single integral with finite limits and an integrand composed solely of trigonometric functions. Assessing the asymptotic (high signal-to-noise ratio) behavior of SEP formulas, we show that the distributed-Alamouti codes achieves a full diversity order. We also perform Monte-Carlo simulations to validate the analysis.
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| 4. |
- Mansouri, Kamel, et al.
(författare)
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CoMPARA : Collaborative Modeling Project for Androgen Receptor Activity
- 2020
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Ingår i: Journal of Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 128:2, s. 1-17
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling.OBJECTIVES: In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP).METHODS: The CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast (TM) metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast (TM)/Tox21 HTS in vitro assays.RESULTS: The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set.DISCUSSION: The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of similar to 875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program's Integrated Chemical Environment.
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