Cross-layer optimization device based on spectrum aggregation in wireless network and method thereof

A spectrum aggregation and wireless network technology, which is applied in the field of cross-layer optimization devices, can solve problems such as the organic integration of spectrum aggregation technology and wireless multi-hop communication, and achieve the effects of increasing effective capacity, improving efficiency, and avoiding complexity

Active Publication Date: 2017-11-21
NORTHEASTERN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0015] The existing work only considers the use of a single spectrum, and does not consider t

Method used

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  • Cross-layer optimization device based on spectrum aggregation in wireless network and method thereof
  • Cross-layer optimization device based on spectrum aggregation in wireless network and method thereof
  • Cross-layer optimization device based on spectrum aggregation in wireless network and method thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0044] Example 1, such as figure 2 shown

[0045] A method for applying a cross-layer optimization device based on spectrum aggregation in a wireless network includes the following steps:

[0046] Step1: Each user node executes the spectrum sensing algorithm to obtain a set of available spectrum fragments, where the available spectrum set of any user i (i∈N) is M i ;

[0047] Step2: Collect the maximum available power of each user, where the maximum available power of any user i(i∈N) is P i max ;

[0048] Step3: Based on the perceived spectrum fragment set and the maximum available power of each user, perform an integer-real-number joint coding method to generate T individuals.

[0049] Step4: Calculate the fitness value of each individual in the initialization population sequentially according to the individual fitness value evaluation method;

[0050] Step5: Use the genetic algorithm to perform genetic evolution operations on the generated population in order to impro...

Embodiment 2

[0052] Example 2, such as image 3 shown

[0053] In the above method, the population initialization method based on the joint coding of integer and real numbers in Step3 can adopt the following steps:

[0054] Step3-1: For any user i(i∈N), get the users neighbor node set N i , and set r=1;

[0055] Step3-2: Initialize the distribution node set A cur =N;

[0056] Step3-3: From A cur Choose a node i(i∈N) among them, and allocate communication channels to its neighbor nodes in turn, and the allocation method is:

[0057] (1) M cur = M i ∪{0},P left =P i max;

[0058] (2) From N i Randomly select a neighbor node j; determine the available channel intersection M of node i and node j ij = M cur ∩ M j ; from set M ij ∪{0} randomly selects a channel c and assigns it to node j;

[0059] (3) If c is not equal to 0, then M cur = M cur \c, indicates the power allocation of the communication link between node i and node j on channel c

[0060] (4) If M cur If it is n...

Embodiment 3

[0064] Example 3, such as Figure 4 shown

[0065] The individual fitness value evaluation method in the above method, this method is mainly based on the given resource allocation results, completes the solution of the routing optimization of each individual in the population, and uses the solved objective function as the fitness value of each individual; the specific steps are as follows:

[0066] Step4-1: Topology construction; mainly based on the resource allocation between nodes and neighbor nodes, complete the construction of the directed graph, where if the channel allocated between node i and its neighbor node j is not 0, and the allocated power is not 0 , there is a directed link from node i to node j;

[0067] Step4-2: Calculate the capacity of each directed link in the topology graph according to the spectrum aggregation relationship, select e ij ∈E, extract link e from individual encoding ij The assigned channel set;

[0068] Step4-3: Calculate the SINR value of...

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Abstract

The invention discloses a cross-layer optimization device based on spectrum aggregation in a wireless network and a method thereof. A genetic algorithm is utilized. Furthermore through mapping resource distribution to individual codes of the genetic algorithm, complexity in performing optimization settlement by means of a physical interference model is effectively prevented, and a requirement for large-scale wireless network optimization is satisfied. In a genetic evolution operation, because a fact that an individual satisfies an optimization restraining condition is always ensured in an individual initialization process and a group evolution process, thereby greatly improving convergence speed and improving optimal solution finding efficiency.

Description

technical field [0001] The present invention relates to a cross-layer optimization device and method based on spectrum aggregation in a wireless network. By fully considering the characteristics of spectrum aggregation in improving link capacity, and fully considering the matching relationship between resource allocation and routing, it has better overall performance. Optimize the effect. Background technique [0002] Different from traditional wireless networks based on single-hop (such as cellular networks and WiFi networks), wireless multi-hop networks have the characteristics of self-organization, self-repair, multi-hop cascading, high speed, and wide coverage. Many aspects, such as increasing network capacity and reducing initial investment, have shown great advantages, and are attracting widespread attention from academia and industry. [0003] With the development of wireless technology, the number of users continues to increase, and the demand for service quality co...

Claims

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Application Information

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IPC IPC(8): H04W16/10H04W16/18H04W24/02H04W40/10H04W72/04
CPCH04W16/10H04W16/18H04W24/02H04W40/10H04W72/0453H04W72/0473Y02D30/70
Inventor 贾杰陈剑刘忠禹范润贤王兴伟
Owner NORTHEASTERN UNIV
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