1 Introduction:

A mobile radio channel is characterized by a multipath fading environment. In other words, the signal offered to the receiver contains not only a direct line of sight radio wave, but also a large number of reflected radio waves that arrive at the receiver at different times. Delayed signals are a result of reflections from terrain features, such as, trees, hills, mountains, vehicles, or buildings. These reflected delayed waves interfere with the direct wave, causing intersymbol interference (ISI), which causes significant degradation of the network performance. A wireless network must be designed to minimize these adverse effects.

For broadband multimedia mobile communication systems, it is necessary to use high bit rate transmission of at least several megabits per second[1,8]. However, if digital data are transmitted at a rate of several megabits per second, the delay time of the delayed waves exceeds 1 symbol time. Because the delayed waves interfere with other symbols, the effects of this interference must be eliminated in the received signal. There are several ways to achieve this goal, for example, adaptive equalization techniques[3,7] at the receiver is one way to equalize the received signal. However, in practice, achieving this equalization at several megabits per second with compact and low cost hardware is quite difficult.

To overcome such a multipath fading environment and achieve a wireless broadband multimedia communication system (WBMCS), it is possible to use an OFDM transmission scheme based on a parallel data transmission scheme that reduces the effects of multiath fading and avoids complex equalizers[5,6,9].

OFDM is expected to be used in future broadcasting and wireless LAN(WLAN)systems. For example, ETSI BRAN in Europe, IEEE802.11 in the United States, and ARIB MMAC in Japan have already adopted the OFDM transmission technology as a physical layer for future broadband WLAN systems. Little work has been previously done on multiuser OFDM. It was first presented by Wahlqvist , who suggested one possible implementation, using FFT structures[5,6]. The system design of a multi-user OFDM system is dependent on the intended application and hardware complexity.

2 Transmitter Configurations:

In the transmitter, the transmitted high –speed data is first converted into parallel data of N subchannels. Then, the transmitted data of each parallel subchannel is modulated by PSK- based modulation[8]. Then modulated data is fed into an inverse fast fourier transform ( IFFT ) circuit , and an OFDM signal is generated [4]. The transmitted data is given by

(1)

Where T_s is the symbol duration of the OFDM signal , and f_i ( I = 0,1,2,3,…. ) is the frequency of the ith sub carrier. Here, f(t) is the pulse waveform of each of the symbols .This OFDM signal is fed into a guard time insertion circuit to reduce ISI [3].

3 Receiver Configurations:

At the receiver, received signal r(t) is filtered by a band pass filter, which is assumed to have sufficiently wide passband to introduce only negligible distortion in the signal. An orthogonal detector is then applied to the signal where the signal is down converted to the IF band[5]. Then, an FFT circuit is applied to the signal to obtain Fourier coefficients[7] of the signal in observation periods [ iT_total , i T_total + T_s ] . The output, d_i(k), of the FFT circuit of the ith OFDM subchannel is given by

(2)

If we estimate the characteristics of the delayed wave, h_i(k) , in a multipath fading environment , we can equalize the received data as follows :

(3)

Where * indicates the complex conjugate.

By comparing d_k and d_i(k) , we can calculate the BER performance . The BER depends on the level of the receiver’s noise. In OFDM transmission, the orthogonality is preserved, and the BER performance depends on the modulation scheme in the sub channel.

4 Proposed System Model:

The modeling have been implemented by using the concepts of UML[2],through Matlab. This will help in making efficient embedded systems. The UML is a common diagrammatic language. Wherever there are computers and computerized systems, there has to be software to drive them. People have to maintain and update it for future versions. It is this human aspect of programming that calls for modeling complex systems on levels of abstraction that are higher than that of “normal” programming languages. From this, also come the need for methodologies to guide software engineers and programmers in coping with the modeling process itself. UML is a standard way to draw various views of a piece of software: the user's view, the architecture, the internal structure of the software, the source code, and the hardware involved. Hence UML is a language of diagrams and gives support for validation [2].

In this proposed method of OFDM.the frame is divided into two parts: channel estimation (CE) symbol and transmitted data symbols. This method uses one CE symbol and six transmitted symbols as one frame unit. In the CE symbol, the amplitude and phase deviation from the pilot data have been measured using the pilot signal. Based on the measured propagation, the deviation of the amplitude and phase of the six OFDM data symbols caused by multipath fading is compensated for. The fluctuation of amplitude and phase due to fading can be compensated by this new, proposed, OFDM modulation scheme .Pilot symbols are inserted at the transmitter at fixed time intervals, using FEC(Forward error correction), based on convolutional coding and soft decision Viterbi decoding. As the level of fluctuation is independent in each subcarrier channel, pilot carriers have been inserted in all frequency domains at a known time period. Then, by using the estimated channel characteristics, the transmitted data have been recovered. Fifty-two subcarriers are adopted and generated by a 64-point FFT circuit. Of the 52 subcarriers, 48 are used for the information data. The rest are used to compensate for the phase noise. To avoid the effects of multpath fading where delay time is greater than the symbol length, a cyclically extended signal have been inserted before each OFDM signal. Guard intervals of 800 ns have been considered, because we must consider using the OFDM based wireless communication system for not only an indoor environment but also in an outdoor microcellular environment. For a 5-Ghz environment, an interval of 800 ns is enough to cover major delayed waves. The sampling rate (20 MHz) was the same as the input signal rate of the IFFT input signal. The coherent detection-based modulation schemes-such as BPSK, QPSK,8PSK and 16-QAM-have been used to improve the quality of the transmitted data and preserve robustness against multipath fading .Forward error correction (FEC) based on convolutional coding and soft decision Viterbi decoding have been used in implementation.

5 Simulation Analysis for Proposed System:

To evaluate the system performance, BER probability is simulated alongwith PER , in which the packet is defined as the number of transmitted data bits in one frame unit. If more than one of these transmitted data bits in one frame makes a mistake, a packet error occurs(fig 2).

The simulation parameters used are: Number of parallel channel, FFT length, number of carriers, number of OFDM symbol for one loop, modulation level, OFDM symbol rate, and

br=sr.m1; % bit rate per carrier

gilen=16; % length of guard interval

ebn0=3; % EbN0

For initializing, the fading parameters used are: time resolution, arrival time, mean power of each multipath, number of waves to generate fading, initial phase of delayed wave, Doppler frequency and

%CE data generation

kndata=zeros(1,fftlen);

kndata0=2.*(rand(1,52)>0.5)-1;

kndata(2:27)=kndata0(1:26);

kndata(39:64)=kndata0(27:52);

ceich=kndata; %CE:BPSK

ceqch=zeros(1,64);

The data have been inserted in the time domain before information OFDM data.

By using the above phase compensation in our computer simulation, we obtained the BER and PER. The BER performance is shown in fig.1, together with the theoretical value. From the BER performance under one-path Rayleigh fading, we found that if we can compensate for the amplitude and phase fluctuations caused by fading, and can obtain a 0.9691-dB shift from the theoretical value. However, if we cannot compensate for the fluctuations, we cannot recover the data. On the other hand, if we use a pilot signal-assisted OFDM transmission scheme, we can obtain a 2-dB shift from the theoretical value. Fig1 shows the simulated BER performance when there is perfect compensation for the amplitude and phase fluctuation caused by propagation characteristics in a one-path fading environment. For the case of perfect compensation, the value of BER was the same as that obtained in the pilot-assisted OFDM system. This means that the BER shifted 2 dB compared to the theoretical value. This was because we input pilot data of 1/7 in one frame unit. As a result, as the number of inserted pilot data symbols increased, the performance degraded and BER performance became even worse when we inserted the guard.In a two-path channel, the BER performance of the pilot signal-assisted OFDM system partly depends on the position of the delayed wave in two-path Rayleigh fading. If the delay time of the delayed wave is shorter than the guard interval, all fluctuations of the amplitude and phase can be removed by using pilot singals, and the BER performance is the same as that in one-path Rayleigh fading. However, if the delay time is longer than the guard integral, ISI contaminates the next symbol and the BER performance degrades.

Fig. 1: BER performance of OFDM (QPSK modulation)using perfect and CE compensation under AWGN and Rayleigh Fading

Fig. 2: PER performance of OFDM (QPSK modulation) using perfect and CE compensation under AWGN and Rayleigh fading environment

6 Comparisons of OFDM Techniques:

The following charts shows comparison of BER performance of different modulation techniques in Rayleigh fading environments. In the receiver, the received signal is fed into the digital demodulator and down converted to base band digital data. For conversion, the method where the received signal on the carrier frequency band is converted to the IF band, and then converted to the base band is popular. Then, on the baseband, the level of amplitude, frequency, or phase is detected for the AM, FM, and PM schemes, respectively, and finally the transmitted digital data is recovered. The BER is a important parameter in mobile communication for quality measurement of recovered data. These PSK schemes are the basis of every digital modulation and transmission scheme. The comparison below shows the BER of each modulation scheme. It is observed that different modulation techniques struggles neck to neck for getting low BER ,but still with the slight change in BER the quality changes many folds. If the PSK techniques are used in designing the wireless transmitter then BER further increases due to system complexity and loading of amplifiers. Therefore, the requirement of designing the new applications/transmission system having the basis as PSK modulation, so that BER atleast remains constant, if not decreases, have been fulfilled/implemented here. Using this new proposed OFDM system with channel estimation ,it is proved that BER is lowest i.e3.685e-004,with Eb/No of 25(Table 1).

OFDM Technique	Eb/No	BER
QPSK Modulation with 128 parallel channel with no compensation[8]	0	4.926e-001
	5	4.909e-001
	15	4.927e-001
	25	4.937e-001
QPSK Modulation with 128 parallel channel with perfect compensation[1,8]	0	1.530e-001
	5	6.467e-002
	15	6.518e-003
	25	6.783e-004
QPSK Modulation with 256 parallel channel with no compensation[8]	0	4.667e-001
	5	4.624e-001
	15	4.670e-001
	25	4.686e-001
Proposed QPSK Modulation with 256 parallel channel with perfect compensation	0	1.456e-001
	5	5.884e-002
	15	3.792e-003
	25	6.184e-005
Proposed OFDM technique using QPSK modulation under CE(Channel Estimation) compensation with 128 parallel channels	0	2.691e-001
	5	1.384e-001
	15	1.791e-002
	25	3.685e-004
LMS(Least Mean Square) technique using QPSK Modulation with 128 parallel channels[8]	0	4e-001
	5	2e-001
	15	6.5e-002
	25	0.9e-002
LMS technique using BPSK Modulation with 128 parallel channels[8]	0	3e-001
	5	0.7e-001
	15	2.4e-002
	25	7e-003

Table 1: Comparison of BER performance of different OFDM techniques in Rayleigh fading environment

7 Conclusions:

For performance analysis BER is chosen, as BER can be evaluated by changing the following parameters (i.e; BER is a superset of following sets)

a) Receiver noise level ,b) Level of received signal ,c) Fading environment ,d) Level of interference signals.

This paper describes the concept behind parallel data transmission and the configuration of an OFDM transmitter and receiver. Proposed OFDM transmitter and receiver configuration, using computer simulation have been implemented. Broadband WLAN system of the future by using a pilot symbol-assisted OFDM transmission system has been implemented. The effectiveness of the proposed OFDM transmission system has been shown in terms of BER.The BER at Eb/No 25 is only 6.184e-005 for proposed QPSK Modulation with 256 parallel channel with perfect compensation and , 3.685e-004 for proposed OFDM technique using QPSK modulation under CE(Channel Estimation) compensation with 128 parallel channels.

Futher, communications research and current development of OFDM around the world will certainly provide us with valuable findings in theory and implementation. Further studies should be conducted on the synchronization of OFDM signal, power demand, counter-measures against frequency offset, fading and multiple accesses.

References:

[1] Coleri Sinem, Ergen Mustafa, Puri Anuj, and Bahai Ahmad, “Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems” IEEE Transactions on Broadcasting, Vol. 48, No. 3, September 2002, pp.223-229

[2] Douglass Bruce Powel, “Real Time UML-Advances in the UML for Real-Time Sytems”,ThirdEdition,Education,ISBN-81-297-0522-2

[3] Goeckel Dennis L., “Adaptive Coding for Time-Varying Channels Using Outdated Fading Estimates”, IEEE transactions on Communications, Vol. 47, No. 6, June 1999, pp. 844

[4] Ma Xiaoli, “Low-Complexity Block Double-Differential Design for OFDM with Carrier Frequency Offset”, IEEE transactions on communications, Vol. 53, No. 12, December 2005, pp.2129

[5] Murphy Charles D., “Low-Complexity FFT Structures for OFDM Transceivers”, IEEE Transactions on Communications, Vol. 50, No.12, December 2002, pp.1878

[6] Ochiai Hideki, and Imai Hideki, “On the Distribution of the Peak-to-Average Power Ratio in OFDM Signals”, IEEE transactions on communications, Vol. 49, No.2, February 2001, pp.282

[7] Qiu Xiaoxin and Chawla Kapil, “On the Performance of Adaptive Modulation in Cellular Systems”, IEEE Transactions on Communications, Vol. 47, NO. 6, June 1999, pp. 884

[8 ] Rappaport Theodore s., Fung Victor, “Simulation of Bit Error Performance of FSK,BPSK, and π/4 DQPSK in Flat Fading Indoor Radio Channels Using a Measurement –Based Channel Model’, IEEE Transactions on Vehicular Technology, Vol.40, No.4, November 1991, pp.731

[9] Yang Baoguo, Letaief Khaled Ben, Cheng Roger S. and Cao Zhigang, “Channel Estimation for OFDM Transmission in Multipath Fading Channels Based on Parametric Channel Modeling”,IEEE transactions on Communications, Vol. 49, No.3, March 2001, pp. 467

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