Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userDSTC Layering Protocols in Wireless Cooperative Networks
107
0
0.0
(
0
)
Added by
Pannir Selvam Elamvazhuthi
Publication date
2009
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
In a radio network with single source-destination pair and some relays, a link between any two nodes is considered to have same or zero path loss. However in practice some links may have considerably high path loss than others but still being useful. In this report, we take into account signals received from these links also. indent Our system model consists of a source-destination pair with two layers of relays in which weaker links between source and second layer and between the first layer and destination are also considered. We propose some protocols in this system model, run simulations under optimum power allocation, and compare these protocols. We show that under reasonable channel strength of these weaker links, the proposed protocols perform ($ approx 2$ dB) better than the existing basic protocol. As expected, the degree of improvement increases with the strength of the weaker links. We also show that with the receive channel knowledge in relays, the reliability and data rate are improved.
rate research
Read More
The theory of wireless information and power transfer in energy constrained wireless networks has caught the interest of researchers due to its potential in increasing the lifetime of sensor nodes and mitigate the environment hazards caused by conventional cell batteries. Similarly, the advancements in areas of cooperative spectrum sharing protocols has enabled efficient use of frequency spectrum between a licensed primary user and a secondary user. In this paper, we consider an energy constrained secondary user which harvests energy from the primary signal and relays the primary signal in exchange for the spectrum access. We consider Nakagami-m fading model and propose two key protocols, namely time-splitting cooperative spectrum sharing (TS-CSS) and power-sharing cooperative spectrum sharing (PS-CSS), and derive expressions for the outage probabilities of the primary and secondary user in decode-forward and amplify-forward relaying modes. From the obtained results, it has been shown that the secondary user can carry its own transmission without adversely affecting the performance of the primary user and that PS-CSS protocol outperforms the TS-PSS protocol in terms of outage probability over a wide range of Signal to noise ratio(SNRs). The effect of various system parameters on the outage performance of these protocols have also been studied.
We show that compact fully connected (FC) deep learning networks trained to classify wireless protocols using a hierarchy of multiple denoising autoencoders (AEs) outperform reference FC networks trained in a typical way, i.e., with a stochastic gradient based optimization of a given FC architecture. Not only is the complexity of such FC network, measured in number of trainable parameters and scalar multiplications, much lower than the reference FC and residual models, its accuracy also outperforms both models for nearly all tested SNR values (0 dB to 50dB). Such AE-trained networks are suited for in-situ protocol inference performed by simple mobile devices based on noisy signal measurements. Training is based on the data transmitted by real devices, and collected in a controlled environment, and systematically augmented by a policy-based data synthesis process by adding to the signal any subset of impairments commonly seen in a wireless receiver.
Multicasting is a fundamental networking primitive utilized by numerous applications. This also holds true for cognitive radio networks (CRNs) which have been proposed as a solution to the problems that emanate from the static non-adaptive features of classical wireless networks. A prime application of CRNs is dynamic spectrum access (DSA), which improves the efficiency of spectrum allocation by allowing a secondary network, comprising of secondary users (SUs), to share spectrum licensed to a primary licensed networks comprising of primary users (PUs). Multicasting in CRNs is a challenging problem due to the dynamic nature of spectrum opportunities available to the SUs. Various approaches, including those based in optimization theory, network coding, algorithms, have been proposed for performing efficient multicast in CRNs. In this paper, we provide a self-contained tutorial on algorithms and techniques useful for solving the multicast problem, and then provide a comprehensive survey of protocols that have been proposed for multicasting in CRNs. We conclude this paper by identifying open research questions and future research directions.
With the seamless coverage of wireless cellular networks in modern society, it is interesting to consider the shape of wireless cellular coverage. Is the shape a regular hexagon, an irregular polygon, or another complex geometrical shape? Based on fractal theory, the statistical characteristic of the wireless cellular coverage boundary is determined by the measured wireless cellular data collected from Shanghai, China. The measured results indicate that the wireless cellular coverage boundary presents an extremely irregular geometrical shape, which is also called a statistical fractal shape. Moreover, the statistical fractal characteristics of the wireless cellular coverage boundary have been validated by values of the Hurst parameter estimated in angular scales. The statistical fractal characteristics of the wireless cellular coverage boundary can be used to evaluate and design the handoff scheme of mobile user terminals in wireless cellular networks.
An energy cooperation policy for energy harvesting wireless sensor networks (WSNs) with wireless power transfer is proposed in this paper to balance the energy at each sensor node and increase the total energy utilization ratio of the whole WSNs. Considering the unbalanced spatio-temporal properties of the energy supply across the deployment terrain of energy harvesting WSNs and the dynamic traffic load at each sensor node, the energy cooperation problem among sensor nodes is decomposed into two steps: the local energy storage at each sensor node based on its traffic load to meet its own needs; within the energy storage procedure sensor nodes with excess energy transmit a part of their energy to nodes with energy shortage through the energy trading. Inventory theory and game theory are respectively applied to solving the local energy storage problem at each sensor node and the energy trading problem among multiple sensor nodes. Numerical results show that compared with the static energy cooperation method without energy trading, the Stackelberg Model based Game we design in this paper can significantly improve the trading volume of energy thereby increasing the utilization ratio of the harvested energy which is unevenly distributed in the WSNs.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
