Intelligent network optimization technology of wireless local area network

Intelligent network optimization technology of wireless local area network

Abstract: In recent years, the wireless LAN technology based on the IEEE802.11 standard series has developed rapidly. However, as the number of access points (APs) continues to increase and the distance between APs continues to decrease, interference in the same frequency band will seriously affect the total capacity of the wireless LAN. The traditional cell network optimization method is no longer applicable to wireless local area networks. This is because the number of wireless local area network APs is large, and the structure may not be stable, that is, APs may increase, decrease, or even move according to business needs. Intelligent network optimization technology means that by dynamically allocating frequency, power, users, and business traffic between APs, the entire wireless network has the largest capacity and the best performance. It will be one of the key technologies for future wireless LAN applications. This article introduces the content, development status and development direction of intelligent network optimization technology.

Keywords: wireless local area network, intelligent network optimization, WLAN, 802.11b AP (Access Point), DFC, TPC

1. Development trend and technical requirements of wireless LAN

WLAN is the abbreviation of wireless local area network, and is a rapidly developing wireless data communication technology in recent years. Its development started from the formulation of the first WLAN standard IEEE802.11 [1] in June 1997, and in August 1999, IEEE introduced new high-speed standards 802.11b [2] and 802.11a into rapid development. IEEE802.11b provides a maximum rate of 11Mbps in the 2.4GHz band; IEEE802.11a provides a data transmission rate of 54Mbps in the 5.8GHz band. In November 2001, IEEE experimentally approved 802.11g to be compatible with 802.11b and 802.11a. At about the same time, the Broadband Radio Access Network (BRAN) team of the European Telecommunications Standardization Institute (ETSI) also set out to develop Hiper (High Performance Radio) access standards and introduced HiperLAN1 and HiperLAN2.

The technological breakthroughs of the IEEE802.11 and HiperLAN families and the dramatic drop in the cost of WLAN products have enabled wireless local area networks to play an important role in broadband wireless access. Not only do enterprises regard WLAN as an extension of their wired LAN, airports, hotels, conference centers, and coffee Halls and other places will also become the focus of WLAN applications. As of now, WLANs using 802.11b and HiperLAN1 have covered more and more regions in North America and Europe. According to expert predictions, the total sales of the global WLAN market will reach nearly US $ 2.2 billion in 2004, with an average annual growth rate of up to about 25%. At the same time, the scope of WLAN applications continues to expand, not only expanding the wired LAN, or even replacing it in some cases.

As the demand for wireless data services increases, in the future, it is not enough to have only one or two or three WLAN access points (APs) in most hotspot areas. Therefore, in areas where services are busy, a small wireless network that can meet the bandwidth requirements of services needs to be deployed. The characteristics of this kind of network are: the number of APs in the network is relatively large; the position of the AP is relatively uncertain, and may be increased, decreased or moved according to needs.

Due to the relatively large number of APs and relatively few available frequency bands (in the 802.11b / g standard, there are only 3 independent and non-interfering frequency bands), there will be mutual interference between some APs. The closer the distance between them, the greater the impact on system capacity. How to allocate frequency and power resources between APs so that the minimum interference and maximum capacity between APs is one of the key technologies that must be solved: wireless network optimization.

The existing 2G network optimization mainly uses a combination of cell modeling calculation and field drive test, but this method is not feasible for WLAN. Because the characteristics of WLAN are: the large number of network nodes, which greatly increases the workload of modeling and drive testing; the number and location of nodes may change, resulting in the above-mentioned network optimization work often need to be repeated.

Under the demand of this background, intelligent network optimization technology will become a new research hotspot. Intelligent network optimization technology means that the frequency, power, users and service traffic are dynamically allocated in real time between APs to maximize the capacity and performance of the entire wireless network. It will undoubtedly be the key technology for the future large-scale application of wireless LAN.

Second, the self-interference situation of wireless LAN

1. Frequency resources of wireless LAN

Let's take the most widely used 802.11b standard as an example to explain why there is mutual interference between multiple APs.

We can see that there is partial spectrum overlap between band 1 and bands 2 to 5. The overlap of the spectrum means that there is interference between the two bands. The size of the interference depends on how much the two frequency bands overlap and the spectral characteristics of the transmitted signal. In short, there is no interference between the frequency bands whose number is greater than or equal to 5, and there is interference between the frequency bands less than 5.

2. Specific interference factors between frequency bands

According to the spectral characteristics of the transmitted signal of the 802.11b physical layer, we can estimate the amount of interference between the two bands.

For the integration of the interference spectrum in the frequency band, the interference factor K of the adjacent frequency band can be obtained, that is, if the total signal energy of the adjacent frequency band is unit 1, the energy of the interference signal of this adjacent frequency band received in this frequency band is K (K <1). The following table is a list of interference factors of adjacent frequency bands:

We can see that the interference of adjacent frequency bands is quite large when the band number difference is less than 3, and it can be ignored when it is greater than or equal to 4.

3. Intelligent network optimization

The purpose of network optimization is mainly to reasonably allocate physical resources and network equipment resources, such as frequency allocation, power allocation, user allocation, and business traffic allocation. Through the optimization of resource allocation, the optimization of the performance and stability of the entire network is obtained.

Because the characteristics of wireless local area network are: the number of network access points AP is relatively large; the location of AP is relatively uncertain, and may be increased, decreased or moved according to needs. Therefore, what we need is not one-time network optimization, but real-time optimization based on the actual network situation. This process usually requires no human intervention, so it is called intelligent network optimization.

Intelligent network optimization can be divided into two major components: automatic frequency optimization and automatic power optimization.

1. Automatic frequency optimization

Automatic frequency optimization, also known as dynamic frequency selection DFC (Dynamic frequency selecTIon), refers to a mechanism that dynamically allocates frequency bands to APs in real time to reduce the interference between APs under the condition that network information is obtained through measurement.

From the information obtained by frequency optimization, automatic frequency optimization can be divided into two categories.

The first category is a scheme for frequency band allocation based on user-side measurement information. For example, the DFC scheme in 802.11h falls into this category. Its workflow is as follows:

(1) The AP issues instructions for frequency band measurement;

(2) The mobile terminal MT (Mobile Terminal) receives the instruction to start the measurement of the frequency band interference;

(3) MT submits the measurement results to the AP;

(4) The AP decides whether to change its own channel;

(5) If it decides to change the frequency band, the AP announces to the MT connected to it that it will change the frequency band;

(6) The AP changes the frequency band, and the MT connected to it also changes with it.

(4) in the above mechanism is not specified in the standard, so a lot of research has focused on how to design a decision algorithm to make the allocation of frequency bands better and more stable and effective.

The advantage of the above mechanism is that the frequency band allocation scheme can be adjusted in real time with the number and location of users. However, the cost of this real-time adjustment is: the user end periodically submits interference reports to the AP; the overhead caused by the AP reconnecting between the user and the AP when switching between frequency bands. As the number of users accessing the AP increases, these two points increase in the same proportion.

There is also a frequency allocation scheme, which is only based on the frequency band measurement of the AP point to adjust the frequency band allocation between the APs. As the number of users connected to the AP increases, considering the mobility of the user, it can be approximated that the user is statistically evenly distributed within the coverage area of ​​the AP, so the frequency band allocation of the AP can be independent of the specific location of the user at a certain moment , Only related to the relative position between APs and mutual interference. This is the second type, a frequency band allocation scheme based on AP measurement information. Its basic workflow is as follows:

(1) AP measures the interference situation under the existing frequency band allocation;

(2) The AP judges the best frequency band by itself;

(3) Distributed adjustment alone or under the direction of the upper controller.

It can be seen that the difference between the second and first categories is as follows: no user terminal is required to participate in the measurement, so it is compatible with all user terminals and does not occupy wireless network traffic; the distribution scheme is only related to the AP, and there is no increase, decrease, or decrease in the AP. In the case of mobile, the allocation scheme generally does not change, so it is very stable and robust; but when the number of users is relatively small, the optimization results are not as good as the first category.

The second type of frequency band allocation scheme based on AP measurement information can be divided into two types according to the adjustment steps. One is distributed adjustment, that is, the APs independently judge and adjust independently, and there is no information interaction between APs. The other is that the AP submits its measurement information to an access controller AC (Access Controler), and the AC controls the AP to make adjustments. In the former one, because there is no information interaction between APs, it may happen that several APs oscillate between several frequency bands, so it is slow to achieve stable convergence. The latter kind of convergence is very fast due to AC coordination.

2. Automatic power optimization

Automatic power optimization mainly includes TPC (Transmit Power Control) for transmitting signals at the user end and power control for transmitting signals at the AP end.

(1) User-side power control is to reduce the user's transmit power as much as possible on the basis of ensuring the user's current communication quality. When the user is relatively close to the AP, since the attenuation of the signal is relatively small, the transmission power of the user can also be relatively small. The advantage of this is that: without affecting the communication quality of this user, it reduces the interference to other users and APs in the same frequency band; reduces the power consumption of the terminal and extends the standby time.

(2) The control of the AP's transmit power is related to the coverage of the AP. Therefore, in general, the AP transmits at the maximum power allowed to cover a larger local area as much as possible, generally about 20dBm (100mW).

But when the number of APs is relatively large, coverage is no longer a problem and mutual interference between APs has become a major problem. For example, a large number of user terminals are concentrated near AP1, but relatively few user terminals are near AP2. When the number of users accessing an AP is greater than a certain number (generally 8), the total channel capacity decreases due to the fierce competition for channels by users. At this time, a better approach is to distribute a part of users closer to AP2 to AP2, so that the number of users of AP1 and AP2 tends to be balanced. This method is also called load balancing. At the beginning, the transmission powers of AP1 and AP2 are equal, as shown by the thin solid line and thick dashed line, so the signals of AP1 received by the four terminals belonging to AP2 at their junction are equal to or greater than the signal of AP2, which is for communication Very unfavorable. After the power optimization of AP1, its coverage is reduced to the thick solid line. At this time, the interference received by the four users belonging to AP2 is significantly reduced. This is the role of AP-end transmit power control with load balancing.

3. Other optimization

In addition to frequency optimization, power optimization, and load balancing, there can also be service traffic balancing, automatic coverage detection, and so on. However, the purpose is to change the AP's transmit frequency band and power at the physical layer, and cooperate with the upper layer to make the entire network have better performance and more stable operation.

4. Conclusion

Automatic frequency optimization, automatic power optimization and load balancing, as well as network traffic balancing, all belong to the category of wireless resource allocation. As people have higher and higher requirements for communication bandwidth, the efficiency of using limited wireless resources will also increase. Therefore, the research on wireless resource allocation has never stopped. In the research of 2G, 3G and post-3G systems, there are researches on wireless resource allocation algorithms.

For different communication systems, the cost function and adjustment means of the wireless resource allocation algorithm are different. Due to the rapid development of wireless local area networks, the need for efficient wireless distribution algorithms has increased, which has attracted the attention of experts and engineers, and will soon become a new research hotspot in wireless local area networks.

The intelligent network optimization scheme is a wireless resource allocation algorithm that conforms to the characteristics and development trends of wireless local area networks. However, the current research only proposes its specific implementation methods [7], and some independent optimization algorithms, including frequency optimization, power optimization and user allocation optimization. We expect that in the near future, we can propose a complete analysis method and optimal solution to the wireless resource allocation of wireless local area networks as a whole and in theory.

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