Remote Sensing Science May 2013, Volume 1, Issue 1, PP.9-14
The LabVIEW Simulation of Space-Time Coding Technique in the MIMO-OFDM System Jiancai Liu#, Shutin Chen, Jiakai Xu College of Electronics Science and Engineering, Nanjing University, Nanjing 210093, P. R. China #
Email: njuliu@163.com
Abstract The space-time coding technology in MIMO system and MIMO-OFDM system is analyzed in this paper. The system performance of the Layered Space-Time Codes (LSTCs), the Space-Time Trellis Codes (STTCs) and the Space-Time Block Codes (STBCs) are studied and compared by means of the LabVIEW simulation, which has also compared the bit error rate (BER) in different signalto-noise ratio (SNR). Several communication systems such as V-BLAST, Trellis and Alamouti coding in different states and different numbers of antennas are simulated by this software. It is proved that the system performance in MIMO system can be effectively improved by means of the space-time coding in BER-SNR graph. We have drawn the conclusion that STTC is the best coding scheme in the three of them. Keywords: MIMO-OFDM; Space-Time Coding (STC); LSTC; STTC; STBC; LabVIEW Simulation
1 INTRODUCTION Orthogonal frequency division multiplexing (OFDM) has attracted a great deal of attention due to its resilience to radio frequency interference, high spectral efficiency, lower multipath distortion and simplified equalization. It has become the basis for the digital audio broadcasting (DAB) and digital video broadcasting (DVB) standards and has been adopted in current WLAN IEEE 802.11a and 802.11g (WiFi) standards [1]. OFDM may be combined with antenna arrays at the transmitter and receiver to increase bandwidth efficiency and/or robustness using multipath signal propagation, resulting in a multiple-input multiple-output (MIMO) configuration. MIMO techniques are now used in the new IEEE 802.11n standard, and will certainly also occur in the forthcoming 802.16e and 3GPP LTE standards. The combination of MIMO and OFDM can achieve a strong reliability through the diversity, and improve the system transmission, which has been regarded as the key technique in the future mobile communication systems [2].
FIGURE 1. MIMO COMMUNICATION USES MULTIPLE ANTENNAS AT BOTH THE TRANSMITTER AND RECEIVER TO EXPLOIT THE SPATIAL DOMAIN FOR SPATIAL MULTIPLEXING AND/OR SPATIAL DIVERSITY.
The theory of space-time coding is studied in this paper and the comprehensive analysis of the LSTC, the STTC and the STBC is made.
2 THE SIMULATION OF THE CHARACTERISTICS OF THE V-BLAST SYSTEM The vertical layered space-time coding scheme in LSTC is simulated by means of the LabVIEW and the V-BLAST -9http://www.ivypub.org/rss
coding scheme. The signal is randomly produced by the system, modulated by the PSK and then coded by the VBLAST. After passing through the Rayleigh flat fadding channel, the signal is added on the Gauss white noise and is finally decoded by the maximum-likelihood (ML) estimation. The SNR is among 0-19. The number of the simulation data for each SNR is 5,000,000. The magnitude of BER for each SNR is statistically counted and the BER-SNR curves are drawn. The MIMO communication uses multiple antennas at both the transmitter and receiver to exploit the spatial domain for spatial multiplexing and/or spatial diversity. Spatial multiplexing has been generally used to increase the capacity of a MIMO link by transmitting independent data streams in the same time slot and frequency band simultaneously from each transmit antenna, and differentiating multiple data streams at the receiver using channel information about each propagation path. In contrast to spatial multiplexing, the purpose of spatial diversity is to increase the diversity order of a MIMO link to mitigate fading by coding a signal across space and time so that a receiver could receive the replicas of the signal and combine those received signals constructively to achieve a diversity gain. The system setting of the transmit and receive antennas is 2T2R，2T4R，4T4R and 4T8R, respectively. Their BER comparisons are shown in Figure 2,
FIGURE 2. THE BER-SNR GRAPH OF THE V-BLAST CODING
It is shown in Figure 2 that the system characteristics can be effectively improved by means of the V-BLAST coding. With the increase of the SNR of the system, the BER decreases linearly. By the comparison of the four schemes, it can be obviously concluded that when the number of the transmit antennas is the same, the greater the number of the receive antennas, the smaller the BER is. When the number of the transmit antennas increases, the BER decreases. In the V-BLAST coding of the MIMO system, we can effectively decrease the system BER and improve the system performance by increasing the number of the antennas of the transmitter and the receiver.
3 THE COMPARISON OF THE CHARACTERISTICS BETWEEN V-BLAST、TRELLIS AND ALAMOUTI The STBC system is simulated by means of the LabVIEW. The signal is randomly produced by the system, modulated by the PSK and then coded by the Trellis. After passing through the Rayleigh flat fadding channel, the signal is added on the Gauss white noise and is finally decoded by the Trellis scheme. The SNR is among 0-19. The number of the simulation data for each SNR is 5,000,000. The BER for each SNR is statistically counted and the BER-SNR curves are drawn. Figure 3 is the simulation of the 4 states and 8 states of the 4PSK of the STTC and the comparison with the STBC. The Space-Time Trellis Codes (STTCs) were first introduced in [4]. These codes combine the space-time mapping principle of STBCs with proper channel coding and thus they provide significant coding gain, in addition to diversity gain. A disadvantage is that their complexity depends on the number of states, which on its turn grows exponentially - 10 http://www.ivypub.org/rss
with the number of transmit antennas. Therefore, the many contributions in literature following [4] are mostly constrained to two, three or four transmit antennas. In general, the incoming bits are first encoded before they are mapped into the space-time format, and modulated. This order perfectly matches that of the general structure of the transmitter of Figure 5. Hence, STTCs fit within the unified view on MIMO systems of this paper.
FIGUER 3. THE COMPARISON OF THE BERS BETWEEN THE STBC AND THE STTC WITH 4 STATES AND 8 STATES
Figure 4 is the comparison of the BERs between the V-BLAST and the Alamouti coding scheme. It is obvious that the Alamouti coding scheme is better than the V-BLAST coding scheme.
FIGURE 4. THE COMPARISON OF THE BERS BETWEEN THE V-BLAST AND THE ALAMOUTI SCHEME
4 THE SYSTEM STRUCTURE OF THE STC COMBINED WITH THE MIMO-OFDM OFDM is an effective and low-complexity strategy for dealing with frequency-selective channels. n OFDM transmitter divides the frequency band into N narrow subchannels and sends a different sequence of symbols across each subchannels. MIMO-OFDM combines OFDM and MIMO techniques thereby achieving spectral efficiency and increased throughput. The OFDM system converts the wideband signal affected by frequency selective fading into some narrow flat fading subchannel signals. The coding is performed over the spatial and temporal dimension in the STC techniques. The technique that combines the OFDM is called STC-OFDM. As is shown in Figure 4, the STC-OFDM transforms the input signal from serials to parallel and modulates the space-time code data from K narrow - 11 http://www.ivypub.org/rss
subchannels (K, the number of subcarriers) respectively. The coding result for the data on each subchannel is always the nT output signals ( nT , the number of transmitter antennas). So, we can get the K groups of output results that includes N subchannel signals. Rearranging the result, we can get all groups of OFDM input signals. After IFFT transformation, the signal outputs from the corresponding antenna. That is to say, the space-time coding is used in the OFDM system. The signal is space-time coded on every subcarriers, and then proceed IFFT modulation. At the receiver, the FFT demodulation is processed and then space-time decoded for the data on each subcarrier. The conventional STC-OFDM scheme which includes arrays of nT transmit and n R receive antennas is illustrated in Figure 5.
FIGURE 5. CONVENTIONAL
nT nR
STC-OFDM SYSTEM: (A) STC-OFDM TRANSMITTER AND (B) STC-OFDM RECEIVER.
In Figure 5, A transmitter shown in Figure 5 (a) begins by encoding a block of symbols to generate a space-time codeword. At time t, the space-time encoder constructs a matrix of nT K modulated symbols given as [1]
x11 2 x X 1 nT x1
x1K xK2 xKnT
x12 x22 x2nT
(1)
Where an element x k belongs to a constellation from M-ary phase-shift keying. The i-th row, i 1,2,, nT , represents a data sequence sent out the i-th transmit antenna. At the i-th transmit antenna, the serial-to-parallel i i i converter allows us to obtain parallel data. OFDM modulation is used to modulate the parallel data, x1 , x2 , x K , by the IFFT. The total available bandwidth of F Hz is divided into K overlapping subcarriers. In the time domain, a cyclic prefix (CP) is added to each OFDM frame during the guard time interval. The length of CP must be larger than the maximum time delay of multipath fading channel such that it can be avoided ISI due to the delay spread of the channel. Consider the receiver shown in Figure 5(b). OFDM demodulation computes the FFT and removes CP. The output of the OFDM demodulator for the k-th subcarrier, k 1,2,, K , and for the j-th receive antenna, j 1,2,, nR , can be expressed in the frequency domain as i
nT
Rkj H kj ,i X ki N kj
(2)
i 1
j ,i
Where H k is the channel frequency response of the k-th subcarrier between the i-th transmit and j-th receive j antennas in the presence of the noise sample N k . The maximum likelihood decoding rule amounts to the computation of nR
K
nT
X arg min Rkj H kj ,i .xki j 1 k 1
i 1
The minimization is performed over all possible space-time codewords. - 12 http://www.ivypub.org/rss
(3)
5 THE VIRTUAL INSTRUMENT (VI) WIRELESS COMMUNICATION SYSTEM MODEL BY THE LABVIEW Here, the Trellis code module is taken as an example. Its code module graph is as Figure 6. The module proceeds encode and modulation for the input sequence according to its state symbol mapping. The number of the transmit antennas and the average symbol energy can be defined. The encode state can be changed according to the following formula: The next state=Input+(The current state*The number of constellations)mod(The number of transmitter antennas) (4) It can be seen in Figure 6 that the input signal is constituted by the second order input signal sequence, the number of transmit antennas, the QAM/PSK option, the average symbol energy, the PSK or QAM constellation size and the state symbol mapping. The output signal is the second order output sequence.
FIGURE 6. THE TRELLIS CODE MODULE GRAPH
The number of the input signal sequences is taken as the ‘For’ cycle number. For every input signal, the next state symbol mapping data corresponding to the current state can be found according to the above encode state formula. The data of its second digit is the transmit signal of the antenna 1 and the data of its first digit is the transmit signal of the antenna 2. They output though their corresponding PSK coding. The Trellis coding module program graph is as Figure 7.
FIGURE 7. THE TRELLIS CODE MODULE PROGRAMME GRAPH
6 CONCLUSION The STC and MIMO-OFDM techniques are studied in this paper. The system functions of LSTC, STTC and STBC in the MIMO system are compared and the virtual wireless communication system model is constructured by means of the LabVIEW software. The environments of different transmitters and different receivers of the V-BLAST coding in LSTC and the Trellis coding in STTC are simulated. We have made a comparison of the BERs in different SNRs, the BERs of the V-BLAST coding in LSTC, the Trellis coding in STTC, as well as the Alamouti coding in STBC. It is verified that the STC in the MIMO of the multi-antenna system can improve the system function effectively. The system functions of different transmit schemes, different number of antennas and different SNRs are analyzed. The communication system that cooperates the STC with the MIMO-OFDM can effciently improve the - 13 http://www.ivypub.org/rss
system capacity, antagonize multi-path interference and be especially suitable for high speed wireless data transmission in frequency selective channels. By means of the LabVIEW system, it is concluded that the BER of the STTC is far lower than the other two cases with the same number of the transmitters, receivers and the systems with the same SNR. The STBC scheme is also obviously better than the V-BLAST scheme of the LSTC.
ACKNOWLEDGMENT This work is supported by the National High-Tech, R&D Program, China (No. 2007 AA11Z228)
REFERENCES [1]
R. van Nee et al., New high-rate wireless LAN standards, IEEE Commun. Mag. (1999) 82-88.
[2]
G.L. Stuber, Broadband MIMO–OFDM wireless communications, Proc. IEEE (2004) 271-294.
[3]
V. Tarokh, H. Jafarkhani, A.R. Calderbank, Space-time block coding for wireless communications: performance results, IEEE J. Select Areas Commun. 17 (1999) 451-460
[4]
V. Tarokh, N. Seshadri, and A. R. Calderbank, Space-time codes for high data rate wireless communication: performance criterion and code construction, IEEE Transactions on Information Theory, Vol. 44, No. 3, March 1998, pp.744-756
[5]
G. L. Stuber, J. R. Barry, S. W. Mclaughlin, Y. Li, M. A. Ingram and T. G. Pratt, Broadband MIMO-OFDM Wireless Communications, Proceeding of the IEEE, Vol.92, No.2, Feb. 2004, pp.271-294
[6]
Z. Li, H. Wei, Cross-layer adaptive modulation and coding design for space-time block coded MIMO-OFDM systems, Computer Communications 32 (2009) 540-545
- 14 http://www.ivypub.org/rss