www.seipub.org/ijc
International Journal on Communications (IJC) Volume 3, 2014
Fractionally Spaced Equalizer for Indoor Visible Light Communication System *Chen Jiaxing1, Zhao Hua1, Jin Huilong1, Li Shaohua2, Lv Qing1, Liu Jinxing3 1.Hebei Normal University, Career Technical College, Hebei Shijiazhuang,050024; 2.The first hospital of Hebei Medical University, Hebei , Shijiazhuang, 050031; 3. Hebei University Of Science and Technology, Department of electronic and communication engineering, Hebei Shijiazhuang,050024 zhaohualunwen@126.com; 213930194955@163.com; 313131145063@163.com;41051388359@qq.com
*1
system.
Abstract Indoor visible light communication, as an emerging broadband wireless access technology, is currently in the stage of scientific research. We can see that indoor visible light communication which is based on white LED lighting technology evolved is often used in LED lighting process to finish data transmission. With the enhancement of scientific research, the interior visible network communication technology is gradually ma-turing, combined with the increasing market demand for increasingly large data, with the demand for mobile broadband communications is in the stage of the rapid growth, therefore, indoor visible light communication technology has been widely gained extensive attention in academia and industry. There-fore, indoor visible light communication te-chnology, which is an important subject of great research value, needs to be made further study. This paper focuses on researching fractionally spaced equalizer for indoor visible light communication system, and studies have shown that equalization of indoor visible light communication -"multipath interference" to the quality of the communication in-terference hadgood inhibitory effect. Keywords Visible Light Communication; Fractionally Spaced; Equalization
Inter-symbol
Interference;
Introduction Access to relevant literature to research and analysis, we can find that current research scholars from various countries in the technical aspects of channel equalization are concentrated in the areas of radio, and rarely study visible indoor channel equalization techniques. Furthermore, applications and transmission channel of optical communication differ from the radio communication. Thus, channel equalization techniques used in radio communications is not available for visible light communication system. For visible light communication system, it requires to develop a new equilibrium technology to suppress the interference. This paper develops fractionally spaced equalizer for indoor visible light communication
54
The Spread of Indoor Visible Light When Indoor visible light communicates, the environment of dissemination of information is different from that of the outdoor, which is airtight, not influenced by wind, the sunshine, the jungle and background light, and the loss in the process of light propagation can be basically ignored. However, when the LED is used as the light source, because of each LED lamp is a light source, with a large number of light source, location and the direction of light propagation are inconsistent, and so it has many different optical signal stream between the signal transmitter and receiver. It is due to the inconsistency of visible light transmission path, which makes different paths to spread the light signal, and the existence of optional path difference, that forms “multipath effect�, the serious inter symbol interference. Related research results shows that, with the existence of inter symbol interference in the visible light communication, the effect of communication will be governed by a certain degree. In order to improve this phenomenon, improve the communication quality of indoor visible light communication technology, it can be used to compensate the channel characteristic by setting equalizer in the receiver so as to improve the ability of the whole system to suppress the inter symbol interference. When adopting the equalizer to make the actual compensation for the channel characteristics, it needs to analyze and research the channel state information in advance, then, using the effective channel equalization to make compensation; therefore, one of the key technologies in the development of visible light communication technology is channel equalization technology. System Model At present, the common visible light communication
International Journal on Communications (IJC) Volume 3, 2014
system is shown in figure 1.
www.seipub.org/ijc
FSE Balancing Algorithm Before adopting FSE channel equalization algorithm to calculate the optical channel, optical receiver will sample the output channel. Sampling process be simplified, T / L of the k-th sampling time period represented in rk. In the above formula x (nT) with x (n) represents, c (t-nt) = c (kT / L-nT) by ck, n represents, ω (t) = ω (kT / L) is represented by ωk. Therefore, using a time signal k can be expressed as: = r(k)
FIG.1 INDOOR VISIBLE LIGHT COMMUNICATION SYSTEM MODEL
Indoor visible communication system model uses the light LED array as a signal transmission source and the signal is unipolar, and adopted intensity modulation / direct detection (IM / DD) as the way of modulation and demodulation. White light signals emitted by the LED lighting are made the intensity-modulation in the signal transmitter (the signal light has an instantaneous power, as same as the binary "1”, no time, and then "0" is the same). The modulated visible light signals at different optical transmission path is transmitted to the signal receiving end, receiving terminal will do direct detection for the received signal, and decode related optical power information so as to export the transmission infor-mation . In this system, the relevant signals mathematically expressed as follows: In the time domain, the indoor and ambient visible light communication signal transmission of visible light can adopt the corresponding real channel impulse function c (t) to describe. Mathematically, the visible light signal received by the signal receiver can be represented by r (t), emitted light signal can be represented by x(t) (x (t) of non-negative), a channel of optical noise can be represented by ω (t), signal convolution can be represented by ⊗ . The relationship between them is: r(t)=x(t) ⊗ c(t)+ω(t)
(1)
In the process of signal transmission, channel noise consists of shot noise and amplifier noise in receiver. Relevant scientific research shows that, in optical communications, on the case of the presence of channel noise, the formula of visible light signal above can be expressed as: in the formula (1) , T is the circle symbol, represents data input symbol in time n, Lk represents a channel length.
L k −1
∑ xn ck ,u + ωk
n =1
(2)
After the signal is acquired, it needs to make a filtering process, which requires to send the signal to the FIR equalizer, an equalizer tap interval of T / L, the signal finishes being filtered needs to be extracted before being outputted by decimation L . Balancing Algorithm In the FIR equalizer, the convolution between the sample sequence and the weight coefficient of equalizer can be expressed sequences of the filtering process by the equalizer, therefore, the output signal of the equalizer can be expressed as: sk =
L • N f −1
∑
i =1
fi rk −i
(3)
Where, fi is fractionally spaced equalizer weights, Nf is the equalizer symbols, L • Nf is the equalizer length. A transmission signal of the equalizer for the sample, sampling the output signal is expressed as: = yn s= Ln
L • N f −1
∑
i =1
fi rLn −i
(4)
The (2) into (4), the matrix expression is obtained sampled output signal: y (n) = (xT (n) C + wT (n)) f (5) FSE Coefficient Optimization When designing the equalizer, using the MMSE criterion, therefore, for the systematic error, the followings will be in accordance with the following formula. e (n) = y (n)-x (n-δ)
(6)
Where, δ is the error in the calculation of the variable, which can be optimized. The (5) into (6), we obtain a formula for the error: e (n) = xT (n) (Cf-hδ) + wT (n) f
(7)
Analyzing the formula (7), using the method of source
55
www.seipub.org/ijc
International Journal on Communications (IJC) Volume 3, 2014
normalization, FSE coefficient minimum, the minimum mean square error, the equalizer coefficient vector and the best delay required to meet the optimization of publicity f = A-1CHhδ, to optimize the results , we know that the minimum mean square error: J= hδH ( I − CA−1C H )hδ MSE
(8)
Computational Analyses An algorithm for calculating the amount of the process is not very precise evaluation of the data, and the evaluation methods used in the computation algorithm is typically bound on the number of basic operations evaluated. In this paper, in order to calculate the Npoint signal input through the fractionally spaced equalizer output after the number of multiplications required to calculate the amount to account for the size, the size of the amount calculated by using the O to measure. Calculating the multiplication by using the FSE method is O ((LN) 2) + O (L3Nf3), the multiplication calculation of the MMSE algorithm in O (N2) + O (Lf3). From the analysis of the above formula, the FSE algorithms to perform a calculation are related of the calculation amount and the size and length of the equalizer sampling interval, and the calculation with two variables constitutes the polynomial. Therefore, a reasonable amount of computation balancing algorithm used in this paper, in practice is feasible.
Simulation Analysis In this paper, computer simulation technology is adopted to evaluate FSE equalization algorithm, and the evaluation index is used in the bit error rate (BER) and mean square error (MSE). Linear relationship (OSNR) between the following picture two and three, respectively, the following figure shows the two equalizers MSE and BER performance and optical signal to noise ratio. As can be seen from the two figures, the spacing of the linear channel equalizer to compensate for inter symbol interference caused by the communication quality does not completely eliminate, but the fractionally spaced equalizer is able to better compensate for the channel distortion of the visible light communication and to suppress inter-symbol interference. Conclusions Indoor visible light communication technology is currently a hot research field of communication, whose technical difficulties should be focused on. For visible light communication technology which is currently due to "multipath effect" caused by communication quality, we use fractionally spaced channel equalization compensation technology research, hoping to promote research and development in related fields. ACKNOWLEDGMENT
1. und Project of Hebei Province Education Office: N2014116. 2. Hebei Normal University Youth Fund Project: L2010Q10. 3. Hebei Normal University Doctoral Fund Project: L2012B15. FIG.2A. OSNR-MSF PERFORMANCE CURVES
REFERENCES
Ding Ju Peng. Indoor visible light communication channel mod-eling and performance optimization [D]. Beijing University of Posts and Telecommunications, 2013. He Shengyang research of key technologies indoor visible light communication system [D]. Harbin Institute of Technology, 2013. Wang Junbo, Xiexiu Xiu, Cao Lingling, Sheng Ming, Feng Min. Indoor visible light communication fractionally FIG.2B. OSNR-BER PERFORMANCE CURVES UNDER TWO EQUALIZATION METHOD DIFFERENT SAMPLING INTERVALS
56
spaced equa-lizer technology [J]. Optics and Precision Engineering,2012,-01:24-30.
International Journal on Communications (IJC) Volume 3, 2014
Xiexiu Xiu Jiao Yuan, Cao Lingling, Feng Min, Sheng Ming. Indoor visible light communication in the linear equalizer
and
decision
feedback
equalizer
[J].
Information Research,2011,-02:29 -32 +38. Zhao Hua (1980.10 -- ), male, Hebei Normal University, Career Technical College, master, lecturer, director of the Department of communication engineering, research direction: the visible light communications, mobile communications, optical fiber communications, weak signal detection-. Address: Shijiazhuang City, Hebei Province, Sou-th Second Ring Road No. 20, zip code: 050024, the mailbox: zhaohualunwen@125.com, Tel: 13483186301. Chen Jiaxing (1977.01-- ), male, Department of science and
www.seipub.org/ijc
technology, Hebei Normal University, Professor,research direction: spread spectrum communication,visible light communication, distributed sensor Jin Huilong (1973.07-- ), male, Hebei Normal University, Career Technical College, Ph. D, associate professor, Dean, research direction: spread spectrum communication, coding theory. Li Shaohua (1982.09-- ), female, the first hospital of Hebei Medical University, master, doctor, lecturer,research direction: medical electronic communication, chronic obstructive pulmonary disease. Lu Qing (1981.06--),female, Hebei Normal University,Career Technical College, PhD, lecturer, research direction: electromagnetic field and microwave technology.
57