Heterogeneous wireless network cooperation coexistence method based on coordination busy tone intelligent protection

Abstract

The invention discloses a heterogeneous wireless network cooperation coexistence method based on coordination busy tone intelligent protection. Targeting a heterogeneous network coexistence problem, the heterogeneous wireless network cooperation coexistence method designs an intelligent coordination busy tone protection strategy, and covers multiple dimensions like frequency, time, space, power, etc. On one hand, the heterogeneous wireless network cooperation coexistence method is compatible with TDMA, CSMA and a mixed access mechanism through early warning and parallel protection, and, on the other hand, the heterogeneous wireless network cooperation coexistence method avoids a monitoring dead zone problem of the coexistence network, expands monitoring ranges of multiple kinds of coexistence networks and network cooperation optimized information quantity; based on an internetwork disturbance classification method of disturbance decoupling and based on a standard that whether the various kinds of networks can monitor a counter party, the heterogeneous wireless network cooperation coexistence method avoids problems of thinking too much or not considering all about the co-existing interference; a busy tone channel is chosen according to a two-end rule and a left-right rule; and on the basis of low expenditure interference signal characteristic extraction, the heterogeneous wireless network cooperation coexistence method performs reasonable protection on a weak network in a coexistence environment and improves comprehensive performance of the coexistence network.

Description

technical field [0001] The invention relates to wireless network technology, in particular to a method for cooperative coexistence of heterogeneous wireless networks based on coordinated busy tone intelligent protection. Background technique [0002] Coexistence is one of the effective means to ensure the performance of wireless sensor networks in the ISM band. According to the "Technical Requirements for Micropower (Short Range) Radio Equipment" promulgated by my country's National Radio Regulatory Commission in 2005, wireless sensor networks work in the ISM frequency band. In addition to wireless sensor networks, wireless devices operating in the ISM frequency band also include microwave ovens, radio frequency identification RFID, cordless phones, Bluetooth, etc. The open and shared nature of wireless channels makes these original devices interfere with wireless sensor networks. In addition, as the application market of wireless sensor networks becomes wider and wider, an...

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Problems solved by technology

[0005] Problem 1: No protocol compatibility

Existing IEEE 802.15.4 and IEEE 802.11 products only implement the functions defined by the protocol itself, but do not realize the compatibility of the two types of protocols. Therefore, IEEE 802.15.4 and IEEE802.11 cannot obtain each other's information, but can only adopt detection methods. Listen mechanism for partial information

[0006] Problem 2: Limited listening range

Therefore, there are cases where the other party cannot be heard

[0007] Problem 3: Large differences in protocols

The radio frequency parameters and access mechanisms of IEEE 802.15.4 and IEEE 802.11 are quite different, which leads to a huge combination of access methods, access frequencies, and access time

At a certain point in time, one network cannot accurately grasp the exact radio frequency parameters and access mechanism of the other network

In particular, most existing IEEE 802.15.4 protocols use an access mechanism combining Time Division Multiple Access (TDMA) and Carrier Sense Multiple Access (CSMA), while IEEE 802.11 cannot perform local distinguish

[0008] In addition, most protocols stipulate the joint access mechanism of CSMA and TDMA. This combination of random and deterministic transmission methods increases the difficulty of joint control.

At the same time, there are many factors that cause multi-network interference. The goal is to maximize the performance of a single network, and it is relatively one-sided to establish a model and design an algorithm for a single key influencing factor. However, considering the joint performance of multiple networks and many influencing factors, the solution space is huge. The problem

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