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1、BER Analysis of Space-Frequency Block Coded MIMO-OFDM Systems using Different Equalizers in Quasi-Static Mobile Radio Channel Bhasker Gupta and Davinder S. Saini Department of Electronics and Communication, Jaypee Univ

2、ersity of Information Technology, Waknaghat, Solan, H.P., INDIA 173215 e-mail: bhasker.gupta@juit.ac.in and davinder.saini@juit.ac.in Abstract-Multiple transmit and receive antennas can be used to form multiple-input

3、multiple-output (MIMO) channels to increase the capacity (by a factor of the minimum number of transmit and receive antennas) and data rate. In this paper, the combination of MIMO technology and orthogonal frequency

4、division multiplexing (OFDM) systems is considered for wideband transmission to mitigate intersymbol interference and to enhance system capacity. It owns the advantages of both MIMO and OFDM. MIMO-OFDM system exploits

5、 the space and frequency diversity simultaneously to improve the performance of system. The coding is done across OFDM sub- carriers rather than OFDM symbols. In this paper, the performance of Space-Frequency (SF) blo

6、ck coding for MIMO-OFDM along with different equalizers is investigated. Bit Error Rate (BER) analysis is presented using different equalizers and then optimum equalization method is suggested. Keywords-MIMO-OFDM; Sp

7、ace-frequency coding; ZF Equalizer; DFE Equalizer; ML Equalizer I. INTRODUCTION The growing demand of multimedia services and the growth of internet related contents lead to increasing interest to high speed com

8、munications. Initially, higher bandwidth was used to support such high data rate applications. However, the increase in bandwidth is an impractical method, and an alternate solution is to adopt some spectral efficien

9、t techniques like MIMO systems [1]. The key advantage of employing multiple antennas is to get reliable performance through diversity and the achievable higher data rate through spatial multiplexing. In MIMO systems,

10、 the same information can be transmitted and received from multiple antennas simultaneously. Since the fading for each link between a pair of transmit and receive antennas can usually be considered to be independent,

11、the probability that the information is detected accurately is higher. Fading of the signal can be mitigated by different diversity techniques, where the signal is transmitted through multiple independent fadin

12、g paths in terms of time, frequency or space and combined constructively at the receiver. OFDM [2] is based on the principle of frequency division multiplexing (FDM), but is utilized as a digital modulation scheme v

13、ia DFT. In OFDM, the entire channel is divided into N parallel narrow subchannels depending upon IFFT size. Thus symbol duration becomes N times longer than in a single carrier system with the same symbol rate. The s

14、ymbol duration is made even longer by adding a cyclic prefix to each symbol. As long as the cyclic prefix is longer than the channel delay spread, OFDM offers inter-symbol interference (ISI) free transmission. Another

15、key advantage of using OFDM is that it reduces the equalization complexity to great extent by enabling equalization in frequency domain. In this paper, we combine multiple transmit and receive antennas for OFDM to fo

16、rm MIMO- OFDM. The air-link architecture of MIMO-OFDM [3] has also been suggested for the future 4G wireless systems. MIMO-OFDM has potential to meet high data rate requirements and high performance over various

17、 challenging channels that may be time-selective and frequency selective. Further, MIMO channels can boost the capacity and the diversity of the system. The rest of the paper is organized as follows. In section II,

18、we introduce MIMO-OFDM transceiver model and briefly review the SF code design criteria. In section III, ST and SF codes are discussed for both 2×1 and 2×2 systems. In section IV, various equalizer algorithm

19、s are presented along with their implementation issues in frequency domain. The simulation results are presented in section V, and some conclusions are drawn in section VI. II. MIMO-OFDM SYSTEM MODEL The general tra

20、nsceiver structure of MIMO-OFDM is presented in Fig. 1. MIMO channel in the presented model consists of 2 transmit and receive antennas. First the incoming data stream is mapped into data symbols via some modulation

21、technique like BPSK, 16-QAM (in this paper).A serial to parallel converter (SPC) coverts the incoming symbols into number of parallel sub-streams. Number of parallel streams depends upon the number of transmitting

22、antennas (2 in this paper). Then a block of say Ng data symbols S= [s1, s2……..sNg] are encoded into a codeword matrix of size NcT×M which will then be sent through M transmit antennas in T OFDM blocks, each block

23、 consisting of Nc subchannels or subcarriers. Where we choose M=2 and Nc=64 for simulation purpose. The codeword matrix [4] can be expressed in “(1)”. C ? ?c?,? c?,? ? c?,M c?,? c?,? … c?,M ? ? ? ? cT,? cT,? ? cT

24、,M? (1) Where C?,? is a vector of length Nc for all j=1.2…M and n=1, 2 ….T. The codeword matrix in (1) can be modified to form SF [5, 6] codeword matrix in “(2)” The input bit stream is divided into

25、b bit long segments, and each segment is mapped onto an SF codeword. Each SF codeword can be represented as an NC×M matrix. 2011 International Conference on Communication Systems and Network Technologies978-0-7695

26、-4437-3/11 $26.00 © 2011 IEEE DOI 10.1109/CSNT.2011.111 520Diversity order can be increased for more reliable communication by employing two receiver antennas on receiver side as in Table II. For some application

27、s, where reliability is of more concern we can increase the diversity order [9] to 2N. N is the number of receiving antennas but the number of transmitting antenna will remain 2. Unfortunately, OSTBC also lacks in pro

28、viding any coding gain and to achieve a rate larger than 3/4 [10] for more than two transmit antennas. In SF scheme, coding is done across antennas and OFDM subchannels. SF coding [11. 12] can be realized by applying

29、 the Alamouti code over two adjacent subchannels in one OFDM block as in Table III. Table III shows that two symbols S0 and –S1*are sent from subchannels K and L of the same OFDM block through transmitting antenna 1.

30、 Similarly symbols S1 and S0*are sent from subchannels K and L of the same OFDM block but through transmitting antenna 2. However, this simple SF coding approach can only achieve space diversity gain, whereas the max

31、imum diversity gain in MIMO- OFDM system will equal to NMD [6]. Where D is number of coherence bandwidths. Research is going on in improving above parameter. IV. EQUALIZATION The inter-symbol interference (ISI) caused

32、 by multipath MIMO channels distorts the MIMO-OFDM transmitted signal which causes bit errors at receiver. To minimize this ISI equalization [13] is needed. Equalizer minimizes the error between actual output and des

33、ired output by continuous updating its filter coefficients. Equalization can be done in both time and frequency domain. Equalization in frequency domain is simpler to use as compared to time domain. In this paper var

34、ious equalizers like ZFE, DFE and ML detection are implemented in frequency domain and their performance evaluation is done in terms of bit error rates (BER). A. Zero-Forcing (ZF) Equalization In ZF equalizer [14] the

35、coefficients are chosen to force the samples of the combined channel and equalizer impulse response to zero. The combined response of the channel with the equalizer is given by “(10)” HCH?f?HEQ?f? ? 1

36、 (10) Where HCH(f) is folded frequency response of the MIMO-channel and HEQ(f) is frequency response of equalizer. Equations (7) and (8) show the combined MIMO- OFDM symbols at receiver 1 and 2. ZF equalizer

37、 can be realized by multiplying the (7) and (8) by vector 1/H(k). Where H(k) is the normalized MIMO-channel vector which can be formed as shown in “(11)”. H ? H??.? H?? ? ? H??.? H?? ? (11) In t

38、his case, the equalizer filter compensates for the channel-induced ISI as well as the ISI brought about by the transmitter and receiver filters. Zero-Forcing filter designed using the equation above does not eliminate

39、 all ISI because the filter is of finite length. B. Decision Feedback Equalizer (DFE) In DFE [15] once an input symbol has been detected, the ISI that it induces on future symbols is estimated and subtracted out befo

40、re detection of subsequent symbols. DFE is realized in direct transversal form which consists of feed forward filter (FFF) and a feedback filter (FBF) as shown in Fig. 2. The FBF [15] is driven by decision on the outp

41、ut of the detector, and its coefficients are adjusted to cancel out the ISI on the current symbol from past detected symbols. RLS (recursive least squares) algorithm is used for determining the coefficient of an adapt

42、ive filter [16]. RLS algorithm uses information from all past input samples to estimate the autocorrelation matrix of the input vector. To decrease the influence of input samples, a weighting factor for the influence

43、 of each sample is used. First process is the filtering in which RLS computes the output of a linear filter in response to an input signal and generates an estimation error. Second is the adjustment of parameters of t

44、he filter in accordance with the estimation error. Reconsider equation 3 and multiply it with weight vector ? ? yields “(12)”. r?n? ? w ? H?n?C?n? (12) Equation (12) describes the filter

45、ing portion of the algorithm. Transversal filter is excited to compute error estimates given by “(13)”.All subscripts are omitted for simplification e?n? ? d?n? ? r?n? (13) Where d?n?

46、 is the desired response and is given by “(14)”.Equation (15) describes the adaptive operation in which the tap-weight vector is updated by incrementing its old value by an amount equal to the complex conjugat

47、e of the estimation error. TABLE I. SPACE TIME SCHEME FOR 2×1 SYSTEMTransmitter antenna 1 Transmitter antenna 2 Time (t) S0 S1 Time (t+T) -S1* S0* TABLE III: SF CODING FOR TWO TRANSMIT ANTENNA OFDM Sub- ch

48、annel K L Transmitting antenna 1 S0 -S1* Transmitting antenna 2 S1 S0* TABLE II: RECEIVED SIGNALS AT TWO RECEIVERS Receiver antenna 1 Receiver antenna 2 Time (t) ? ?? ??? Time (t+T) ? ?? ??? ∑ - Figure 2.

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