This study introduces a decentralized approach to secure wireless communication using a cryptographic secret key generation algorithm among distributed nodes. The system model employs Gaussian prime numbers, ensuring ...
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ISBN:
(纸本)9798350384826;9798350384819
This study introduces a decentralized approach to secure wireless communication using a cryptographic secret key generation algorithm among distributed nodes. The system model employs Gaussian prime numbers, ensuring the collaborative generation of a secret key. Pre-processing and post-processing functions enable to generate a secret key across the network. An error model evaluates aspects like thermal noise power and channel estimation errors, while simulations assess the success rate to factorize the norm of the secret key. It is observed that path loss-induced large scale fading emerges as a critical component impacting information and power loss. The robustness of the proposed model under fading channel conditions is evaluated with a success rate. Additionally, it is also observed that the tolerance value set in the factorization algorithms has a significant impact on the success rate. Furthermore, the success rate is compared in two scenarios, one with 2 users and another with 3 users, to provide a comprehensive evaluation of the system performance.
Conventional analog function computation (AFC) is an effective data aggregation technique that combines communication and computation to improve time efficiency and scalability. In this letter, different from the conv...
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Conventional analog function computation (AFC) is an effective data aggregation technique that combines communication and computation to improve time efficiency and scalability. In this letter, different from the conventional AFC, we study distinguishing individual observations from the aggregated data by including unique prime identifiers to pre-processing functions. Prime identifiers can be used to equip the network with a simple authentication mechanism while removing the dependency on public key algorithms or trusted third parties. The resilience of the proposed scheme to spoofing attacks and non-ideal conditions including the channel estimation errors and the thermal noise is investigated with computer simulations.
analog function computation utilizes the superposition property of multi-access channel to compute the target function in an efficient way. However, its corresponding transceiver requires global channel state informat...
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analog function computation utilizes the superposition property of multi-access channel to compute the target function in an efficient way. However, its corresponding transceiver requires global channel state information (CSI) of the network, which incurs large latency. To tackle this challenge, a novel scheme called over-the-air signaling procedure is proposed by exploiting a defined effective CSI in this paper. We first derive the training complexity of the proposed scheme and compare it with the conventional design. It is shown that the training complexity of the proposed scheme can be greatly reduced for massive CSI acquisition by avoiding collecting individual CSI. To account for the difference of the desired CSI, a corresponding robust model is further discussed. Through modeling the channel uncertainties under the expectation-based model and the worst case model, we formulate the transceiver optimization for both the conventional scheme and the over-the-air signaling procedure. The computational time complexity is derived as a polynomial expression, and it can be significantly reduced for the over-the-air signaling procedure due to its independence of the number of nodes. Finally, the mean-square error improvement and complexity reduction of the proposed design are demonstrated via simulation.
analog function computation utilizes the superposition property of multi-access channel (MAC) to compute the target function in an efficient way. However, its corresponding transceiver requires global channel state in...
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ISBN:
(纸本)9781538676462
analog function computation utilizes the superposition property of multi-access channel (MAC) to compute the target function in an efficient way. However, its corresponding transceiver requires global channel state information (CSI) of the network, which incurs large latency. To tackle this challenge, a novel scheme called over-the-air signaling procedure is proposed by exploiting a defined effective CSI in this paper. We derive the training complexity of the proposed scheme and compare it with the conventional design. It is shown that the training complexity of the proposed scheme can be greatly reduced for massive CSI acquisition by avoiding collecting individual CSI. To account for the difference of the desired CSI, a corresponding robust design is further discussed under the worst-case model. The mean-square error (MSE) improvement and training complexity reduction of the proposed design are demonstrated via simulation.
In this letter, we propose an adaptive analog function computation (AFC) via fading multiple-access channels in which multiple sensors simultaneously send their observations and then the fusion center computes the des...
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In this letter, we propose an adaptive analog function computation (AFC) via fading multiple-access channels in which multiple sensors simultaneously send their observations and then the fusion center computes the desired function via the superposition property of wireless channels. In particular, each sensor adaptively sends its observation to the fusion center based on its causal channel state information (CSI). Numerical results show that the adaptive AFC significantly outperforms the conventional non-adaptive AFC in terms of the outage probability of function estimation error. The adaptive AFC operates in a fully distributed manner with local and causal CSI, applicable to various practical sensor network applications.
For wireless networks which aim at high speed communication and computation, we propose a parallel analog function computation scheme via wireless multiple-access multiple-input-multiple-output channels. We consider t...
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For wireless networks which aim at high speed communication and computation, we propose a parallel analog function computation scheme via wireless multiple-access multiple-input-multiple-output channels. We consider that each sensor node only has imperfect channel state information from itself to the fusion center. Modeling the channel uncertainties by the worst-case model, the robust transceiver design problem for parallel analog function computation is formulated as a non-convex optimization problem which minimizes the worst-case mean-square-error subject to individual transmit power constraints. We then propose an alternating optimization algorithm to solve the problem. Simulation results demonstrate that the proposed robust scheme outperforms the non-robust one.
Future sensor networks require energy and bandwidth efficient designs to support the growing number of nodes. The security aspect is often neglected due to the extra computational burden imposed on the sensor nodes. I...
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Future sensor networks require energy and bandwidth efficient designs to support the growing number of nodes. The security aspect is often neglected due to the extra computational burden imposed on the sensor nodes. In this article, we propose a secret key generation method for wireless sensor networks by using the physical layer features. This key generation method is based on the superposition property of wireless channels. The proposed method exploits the multiple access property of the wireless channel with simultaneous transmissions as in the analog function computation technique to solve the latency and scarce bandwidth problems of highly populated dense networks. All nodes use the same time and frequency block to provide scalability that is linearly proportional to the number of nodes. The proposed method also benefits from the network density to provide security against eavesdroppers that aim to sniff the secret key from the channel. The security of the proposed method against eavesdroppers is analytically studied. Moreover, their application in multiple layers is investigated. The presented results have shown that there is a tradeoff between the total power consumption and total used bandwidth for secret key generation. Lastly, the error probability of the generated keys due to thermal noise and channel estimation error is investigated with computer simulations and compared with broadcasting-based benchmark model.
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