Distributed space-time coding including the golden code with application in cooperative networks

This thesis presents new methodologies to improve performance of wireless cooperative networks using the Golden Code. As a form of space-time coding, the Golden Code can achieve diversity-multiplexing tradeoff and the data rate can be twice that of the Alamouti code. In practice, however, asynchronism between relay nodes may reduce performance and channel quality can be degraded from certain antennas. Firstly, a simple offset transmission scheme, which employs full interference cancellation (FIC) and orthogonal frequency division multiplexing (OFDM), is enhanced through the use of four relay nodes and receiver processing to mitigate asynchronism. Then, the potential reduction in diversity gain due to the dependent channel matrix elements in the distributed Golden Code transmission, and the rate penalty of multihop transmission, are mitigated by relay selection based on two-way transmission. The Golden Code is also implemented in an asynchronous one-way relay network over frequency flat and selective channels, and a simple approach to overcome asynchronism is proposed. In one-way communication with computationally efficient sphere decoding, the maximum of the channel parameter means is shown to achieve the best performance for the relay selection through bit error rate simulations. Secondly, to reduce the cost of hardware when multiple antennas are available in a cooperative network, multi-antenna selection is exploited. In this context, maximum-sum transmit antenna selection is proposed. End-to-end signal-to-noise ratio (SNR) is calculated and outage probability analysis is performed when the links are modelled as Rayleigh fading frequency flat channels. The numerical results support the analysis and for a MIMO system maximum-sum selection is shown to outperform maximum-minimum selection. Additionally, pairwise error probability (PEP) analysis is performed for maximum-sum transmit antenna selection with the Golden Code and the diversity order is obtained. Finally, with the assumption of fibre-connected multiple antennas with finite buffers, multiple-antenna selection is implemented on the basis of maximum-sum antenna selection. Frequency flat Rayleigh fading channels are assumed together with a decode and forward transmission scheme. Outage probability analysis is performed by exploiting the steady-state stationarity of a Markov Chain model

Performance Analysis for Multi-hop Cognitive Radio Networks with Energy Harvesting by Using Stochastic Geometry

Cognitive multihop relaying has been widely considered for device-to-device (D2D) communications for applications in the physical layer of the Internet of Things. In this article, we construct a multihop cellular D2D communications system model with energy harvesting (EH) in underlay cognitive radio networks. The locations of primary user equipments (PUEs) and cellular base stations are considered as a Poisson point process in this model. The transmit power of secondary devices is collected from the power beacon with time-switching EH policy. Two charging policies for different applications are considered in this article. Then, the end-to-end outage probability analysis expressions of these two scenarios for the transmission scheme subject to interferences from PUEs are derived. The optimal harvesting time ratio is obtained to get the maximum capacity for end-to-end D2D communications. The analytical results are validated by performing the Monte Carlo simulation of the end-to-end outage probability, which is based on the half-duplex transmission scheme. The results of this article provide a potential pathway to reduce reliance on grid or battery energy supplies and, hence, further strengthen the benefits for the environment and deployment of future smart devices. </ul

Image_1_Overexpression of Thioredoxin-1 Blocks Morphine-Induced Conditioned Place Preference Through Regulating the Interaction of γ-Aminobutyric Acid and Dopamine Systems.tif

<p>Morphine is one kind of opioid, which is currently the most effective widely utilized pain relieving pharmaceutical. Long-term administration of morphine leads to dependence and addiction. Thioredoxin-1 (Trx-1) is an important redox regulating protein and works as a neurotrophic cofactor. Our previous study showed that geranylgeranylaceton, an inducer of Trx-1 protected mice from rewarding effects induced by morphine. However, whether overexpression of Trx-1 can block morphine-induced conditioned place preference (CPP) in mice is still unknown. In this study, we first examined whether overexpression of Trx-1 affects the CPP after morphine training and further examined the dopamine (DA) and γ-aminobutyric acid (GABA) systems involved in rewarding effects. Our results showed that morphine-induced CPP was blocked in Trx-1 overexpression transgenic (TG) mice. Trx-1 expression was induced by morphine in the ventral tegmental area (VTA) and nucleus accumbens (NAc) in wild-type (WT) mice, which was not induced in Trx-1 TG mice. The DA level and expressions of tyrosine hydroxylase (TH) and D1 were induced by morphine in WT mice, which were not induced in Trx-1 TG mice. The GABA level and expression of GABA_BR were decreased by morphine, which were restored in Trx-1 TG mice. Therefore, Trx-1 may play a role in blocking CPP induced by morphine through regulating the expressions of D1, TH, and GABA_BR in the VTA and NAc.</p

Presentation_1_Overexpression of Thioredoxin-1 Blocks Morphine-Induced Conditioned Place Preference Through Regulating the Interaction of γ-Aminobutyric Acid and Dopamine Systems.PDF

<p>Morphine is one kind of opioid, which is currently the most effective widely utilized pain relieving pharmaceutical. Long-term administration of morphine leads to dependence and addiction. Thioredoxin-1 (Trx-1) is an important redox regulating protein and works as a neurotrophic cofactor. Our previous study showed that geranylgeranylaceton, an inducer of Trx-1 protected mice from rewarding effects induced by morphine. However, whether overexpression of Trx-1 can block morphine-induced conditioned place preference (CPP) in mice is still unknown. In this study, we first examined whether overexpression of Trx-1 affects the CPP after morphine training and further examined the dopamine (DA) and γ-aminobutyric acid (GABA) systems involved in rewarding effects. Our results showed that morphine-induced CPP was blocked in Trx-1 overexpression transgenic (TG) mice. Trx-1 expression was induced by morphine in the ventral tegmental area (VTA) and nucleus accumbens (NAc) in wild-type (WT) mice, which was not induced in Trx-1 TG mice. The DA level and expressions of tyrosine hydroxylase (TH) and D1 were induced by morphine in WT mice, which were not induced in Trx-1 TG mice. The GABA level and expression of GABA_BR were decreased by morphine, which were restored in Trx-1 TG mice. Therefore, Trx-1 may play a role in blocking CPP induced by morphine through regulating the expressions of D1, TH, and GABA_BR in the VTA and NAc.</p