Downlink antenna arraying is an effective method to improve the ground receiving capacity instead of the large-aperture antenna in the future deep space explorations, and that the arraying combining algorithm is the k...
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Using a spatial multiplexing transmission scheme can improve the data rate in multiple-input-multiple-output (MIMO) relaying systems, while making signal detection more difficult at receivers. Aiming at lowering the c...
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Using a spatial multiplexing transmission scheme can improve the data rate in multiple-input-multiple-output (MIMO) relaying systems, while making signal detection more difficult at receivers. Aiming at lowering the computational complexity of the receiver, this paper proposes a maximum likelihood combining (MLC) algorithm for spatial multiplexing MIMO amplify-and-forward (AF) relaying systems in a Rayleigh flat-fading environment, which is implemented before maximum likelihood (ML) detection. The combining signal and equivalent channel are opportunely designed based on the ML rule in the MLC algorithm. We also formulate the diversity gain of the systems that employ the MLC algorithm mathematically, induced by the Chernoff bound of pairwise error probability (PEP). An upper bound on the symbol error probability (SEP) for the MLC algorithm with multiple modulations is also given, based on the derived bound of PEP. Moreover, the complexities of ML receivers adopting the MLC algorithm and the conventional vector combining (VC) algorithm are analyzed. Numerical simulations indicate that systems with the MLC algorithm achieve the same performance while consuming lower computational complexity compared to that with the VC algorithm.
XACML is a standard language for specifying attribute-based access control policies of computer and software systems. It offers a variety of combining algorithms for flexible policy composition. While they are intende...
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ISBN:
(纸本)9781467379892
XACML is a standard language for specifying attribute-based access control policies of computer and software systems. It offers a variety of combining algorithms for flexible policy composition. While they are intended to be different, they also bear similarities. Some combining algorithms can be functionally equivalent with respect to the given policy or policies. To correctly use the combining algorithms, it is important to understand the subtle similarities and differences. This paper presents a formal treatment of the semantic differences between the commonly used combining algorithms in XACML 3.0. For each pair of the selected combining algorithms, we identify when they are functionally equivalent and when they are not equivalent. This rigorous understanding helps minimize incorrect uses of combining algorithms that may lead to unauthorized access and denial of service. It also provides a foundation for determining equivalent mutants of combining algorithms in mutation testing of XACML policies.
With the increasing complexity of software, new access control methods have emerged to deal with attribute-based authorization. As a standard language for specifying attribute-based access control policies, XACML offe...
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With the increasing complexity of software, new access control methods have emerged to deal with attribute-based authorization. As a standard language for specifying attribute-based access control policies, XACML offers a number of rule and policy combining algorithms to meet different needs of policy composition. Due to their variety and complexity, however, it is not uncommon to apply combining algorithms incorrectly, which can lead to unauthorized access or denial of service. To solve this problem, this paper presents a fault-based testing approach for revealing incorrect combining algorithms in XACML 3.0 policies. The theoretical foundation of this approach relies on the formalization of semantic differences between rule combining algorithms and between policy combining algorithms. It allows the use of a constraint solver for generating queries to which a given policy produces different responses than its combining algorithm-based mutants. Such queries can determine whether or not the given combining algorithm is used correctly. Our empirical studies using various XACML policies have demonstrated that our approach is effective.
Weak signal detection is very important for military and civil system. This paper discussed the combining algorithm of coherent integration and probability, the simulation with matlab showed it's advantageous char...
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ISBN:
(纸本)9789881824202
Weak signal detection is very important for military and civil system. This paper discussed the combining algorithm of coherent integration and probability, the simulation with matlab showed it's advantageous characteristics and useful for weak signal detection.
Weak signal detection is very important for military and civil system. This paper discussed the combining algorithm of coherent integration and probability, the simulation with matlab showed it's advantageous char...
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Weak signal detection is very important for military and civil system. This paper discussed the combining algorithm of coherent integration and probability, the simulation with matlab showed it's advantageous characteristics and useful for weak signal detection.
We consider a message-passing system of n processors, each of which initially holds one piece of data. The goal is to compute an associative and commutative census function f on the n distributed pieces of data and to...
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We consider a message-passing system of n processors, each of which initially holds one piece of data. The goal is to compute an associative and commutative census function f on the n distributed pieces of data and to make the result known to all processors. To perform the computation, processors communicate with each other by sending and receiving messages in specified communication rounds. We describe an optimal algorithm for this problem that requires the least number of communication rounds and that minimizes the time spent by any processor in sending and receiving messages.
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