In this paper, a framework is proposed to improve the effectiveness of the long-term-evolution vehicle-to-vehicle (LTE-V2V) communication system, where the uplink channel of the cellular user equipment (CUE) is reused...
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In this paper, a framework is proposed to improve the effectiveness of the long-term-evolution vehicle-to-vehicle (LTE-V2V) communication system, where the uplink channel of the cellular user equipment (CUE) is reused by multiple V2V links. Since the orthogonal channels occupied by each CUEs are multiplexed by multiple V2V links, the serious interference is generated in the co-tier layer and cross-tier layer. In order to minimize the co-channel interference between CUE link and V2V links, an optimized resource sharing scheme is proposed. Firstly, Fuzzy C-means (FCM) algorithm is proposed to perform the clustering based on the geographical location characteristics of V2V links. In the FCM algorithm, the adjacent V2V links are grouped into a cluster to facilitate the solution of the channel allocation problem. Assuring the V2V links in the same cluster do not share the same channel, the adjacent V2V links are avoided to reuse the same channel. On this basis, the use of reasonable channel allocation scheme can effectively reduce the co-channel interference. Considering that the channel state information (CSI) of mobile links is slowly faded, the total system capacity is maximized by leveraging the CSI while the reliability can be guaranteed for all V2V links. The outage probability constraint is used to ensure the reliability of all V2V links. The channel assignment problem of V2V links is formulated as a weighted two-dimensional matching problem, and the interference bipartite graph is constructed. Finally, Kuhn Munkras (km) algorithm is introduced to allocate the uplink orthogonal channel of CUEs for the V2V links in the same class in order to maximize the total system capacity. Numerical simulation results show that the algorithm can improve the total system capacity.
Type reduction does the work of computing the centroid of a type-2 fuzzy set. The result is a type-1 fuzzy set from which a corresponding crisp number can then be obtained through defuzzification. Type reduction is on...
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Type reduction does the work of computing the centroid of a type-2 fuzzy set. The result is a type-1 fuzzy set from which a corresponding crisp number can then be obtained through defuzzification. Type reduction is one of the major operations involved in type-2 fuzzy inference. Therefore, making type reduction efficient is a significant task in the application of type-2 fuzzy systems. Liu introduced a horizontal slice representation, called the alpha-plane representation, and proposed a type-reduction method for a type-2 fuzzy set. By exploring some useful properties of the alpha-plane representation and of the type reduction for interval type-2 fuzzy sets, a fast method is developed for computing the centroid of a type-2 fuzzy set. The number of computations and comparisons involved is greatly reduced. Convergence in each iteration can then speed up, and type reduction can be done much more efficiently. The effectiveness of the proposed method is analyzed mathematically and demonstrated by experimental results.
Relay is a type of application of Device-to-Device (D2D) communication which could optimize the system capacity over the shared uplink (UL) resources while fulfilling prioritized cellular service constrains. In this p...
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ISBN:
(纸本)9781612846835;9781612846828
Relay is a type of application of Device-to-Device (D2D) communication which could optimize the system capacity over the shared uplink (UL) resources while fulfilling prioritized cellular service constrains. In this paper, we consider D2D communication for relay purpose assists User Equipments (UEs) to communicate with Base Station (BS). For constraining the interference from D2D communication to cellular communication in the permitted range by system, we analyze the transmission rate from D2D UE. Further, we deduce a relay selection rule based on the interference constraining. Then, we apply the km algorithm and the greedy algorithm as two types of selection methods to select different relay for every relay-needed UE according to the selection rule. The numerical simulations results show the sum-rate can be improved by selecting the relays according to the selection rule, and km algorithm achieves a slightly higher sum-rate than that of greedy algorithm based on the relay selection rule.
Logistics order distribution is an important part of the sales process of finished steel products, and plays a vital role in the overall experience of the sales process and the virtuous cycle of the whole process. In ...
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ISBN:
(纸本)9781450397773
Logistics order distribution is an important part of the sales process of finished steel products, and plays a vital role in the overall experience of the sales process and the virtuous cycle of the whole process. In the actual production process, the manual order distribution model maintained for a long time seems to have a richer accumulation of experience and knowledge, but in reality it has become difficult to adapt to the development requirements of a long time dimension. In order to fully consider the lowest logistics cost of sales in a time cycle as well as the higher revenue of the carrier driver, while ensuring the long-term revenue of the enterprise, this paper considers multi-objective constraints, establishes Markov decision model, introduces km algorithm to perform dichotomous graph matching, based on the multi-objective optimization for maximizing driver revenue and minimizing enterprise cost, with the long-term ultimate goal of maximizing total steel commodity transaction volume, and finally Combining the value function and the multi-objective optimization function of multiple attributes to form a complete matching decision of vehicles and goods. Using real business data of steel enterprises as an example, the data is pre-processed and then suitable features are screened for model training and the correctness and usability of the algorithm is verified. The results show that the model can better address the needs of steel companies in order allocation scenarios compared to traditional order allocation methods.
The linguistic weighted average (LWA) is an extension of the fuzzy weighted average (FWA).The process of solving LWA can be divided into steps of solving two ***, the commonly used method of FWA is based on α-cut dec...
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The linguistic weighted average (LWA) is an extension of the fuzzy weighted average (FWA).The process of solving LWA can be divided into steps of solving two ***, the commonly used method of FWA is based on α-cut decomposition,which discretizes the [0, 1] interval into several α-cuts and then computes each α-cut as an interval weighted ***, this method involves large amount of calculations, and the result for LWA is not *** this paper, we adopt a new algorithm, analytical solution methods, which is more accurate and *** the end of this paper, we present a numerical example to illustrate the algorithm.
The linguistic weighted average(LWA) is an extension of the fuzzy weighted average(FWA). The process of solving LWA can be divided into steps of solving two ***,the commonly used method of FWA is based onα-cut decomp...
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The linguistic weighted average(LWA) is an extension of the fuzzy weighted average(FWA). The process of solving LWA can be divided into steps of solving two ***,the commonly used method of FWA is based onα-cut decomposition, which discretizes the[0,1]interval into several a-cuts and then computes eachα-cut as an interval weighted ***,this method involves large amount of calculations,and the result for LWA is not *** this paper,we adopt a new algorithm, analytical solution methods,which is more accurate and *** the end of this paper,we present a numerical example to illustrate the algorithm.
A sort method is proposed to enhance the significant spectral components of test set. In the field of integrated circuit testing, to calculate significant spectral components, it's necessary to do spectrum analysi...
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ISBN:
(纸本)9781509040940
A sort method is proposed to enhance the significant spectral components of test set. In the field of integrated circuit testing, to calculate significant spectral components, it's necessary to do spectrum analysis for the test set. In this paper, a bipartite graph and weight matrix are constructed based on the test set and its significant spectral components. Therefore, the problem of enhancement of significant spectrum components is transformed into a bipartite graph matching problem that can be solved by km (Kuhn-Munkras) algorithm. After the order adjustment of the test set according to the matching relationship, the correlation between the significant component and test set has been increased, and the significant spectral components are enhanced. Finally, the experimental results on the test set of the ISCAS-89 benchmark circuits show that the coefficients of the sorted test have increased by 9.47% on average, and the incompatible bits between the test set and its significant spectral components have effectively reduced by 14.18% on average.
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