ESTIMATION AND COMPENSATION OF CARRIER FREQUENCY OFFSET ...iraj.in/journal/journal_file/journal_pdf/1-8-139029620022-28.pdf · Estimation And Compensation Of Carrier Frequency Offset

International Journal of Electrical, Electronics and Data Communication, ISSN: 2320-2084 Volume- 1, Issue- 8, Oct-2013

Estimation And Compensation Of Carrier Frequency Offset (CFO) And Channel Distortion For MIMO OFDM Systems

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ESTIMATION AND COMPENSATION OF CARRIER FREQUENCY OFFSET (CFO) AND CHANNEL DISTORTION FOR MIMO OFDM

SYSTEMS

1NAGESWARA LALAM, 2GAURAV KUMAR PANDEY

University Institute of Technology (UIT), Rajiv Gandhi Technological University, Bhopal Email: [email protected], [email protected]

Abstract— In this paper, proposed a joint estimation of Carrier Frequency Offset (CFO) and Channel Distortion for Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) system using training sequences. Carrier Frequency Offset (CFO) acquisition algorithm and Carrier Frequency Offset (CFO) Tracking algorithm are proposed to improve the estimation accuracy of MIMO OFDM system. The proposed estimation method requires at least one OFDM training block for estimation and training symbols should be random. If the OFDM training block consists of two repeated sequences, a low complexity two step approach used to solve the joint estimation problem. Simulation results show that the Mean Squared Error (MSE) of Carrier Frequency Offset (CFO) and Channel Distortion in proposed methods. Keywords— Carrier-frequency offset (CFO), channel estimation, multiple-input multiple-output (MIMO), orthogonal frequency division multiplexing (OFDM). I. INTRODUCTION Recently, orthogonal frequency division multiplexing (OFDM) has become a wide spread wireless communication technique for transmission of signals through the wireless channels. The key challenge for future wireless communication systems is to provide high data rate access at high quality of service (QoS). Increase the spectral efficiency and improve link reliability. Multiple input multiple output (MIMO) OFDM wireless technology provides to meet these demands [1]. The maturing of MIMO OFDM technology leads to a several applications such as digital video broad casting (DVB), digital audio broadcasting (DAB), the IEEE 802.16a wireless metropolitan area network (WMAN) standard, and IEEE 802.11a wireless local area network (WLAN) standard. OFDM is also used for dedicated shortrange communications and as a potential candidate for fourth generation (4G) mobile wireless communication systems [2]. In MIMO OFDM a collection of problems including carrier frequency offset (CFO), channel distortion and I/Q (in phasequadrature) imbalance can seriously degrade the system performance. Orthogonal frequency division multiplexing (OFDM) is a mostly useful modulation technique for transmission of signals over wireless communication channels. In OFDM systems the available bandwidth is utilized very efficiently without causing the inter-carrier interference (ICI) []. In MIMO OFDM systems multiple antennas have been used at both sides of the wireless link for interference cancellation and realize diversity gain. Orthogonal Frequency Division Multiplexing (OFDM) is a multi channel modulation technique that makes the use of Frequency Division Multiplexing (FDM) of orthogonal multi carriers modulating by a low bit rate digital stream. In other words OFDM is a

method of encoding digital data on multiple carrier frequency. An important technique for an OFDM system is FFT (Fast Fourier Transform) is used for modulation and demodulation of an OFDM systems. For long time OFDM system was used only for military applications. OFDM is a strong technology for fourth generation mobile communication systems and for ultra wideband (UWB) systems. OFDM is also known as the multicarrier modulation and discrete multi tone. The basic principle of an OFDM is dividing the available transmission bandwidth into several parallel narrowband channels. The input data is divided into several data streams or channels. Each channel modulated with a conventional modulation schemes such as quadrature amplitude modulation (QAM) or phase shift keying (PSK) [3]. In OFDM system the sub carriers are orthogonal to each other, So that the cross talk between the sub channels is eliminated and inter carrier guard bands are not required. OFDM orthogonality allows for efficient modulator and demodulator implementation using Fast Fourier Transform (FFT) algorithm on the receiver side and Inverse Fast Fourier Transform (IFFT) on the transmission side. The remained paper organised as follows. In section II, described a MIMO OFDM system model. In section III discussed the Carrier Frequency Offset (CFO) tracking and acquisition algorithms. And in section IV proposed a joint estimation of CFO and Channel Distortion. And Joint Estimation of Carrier Frequency Offset (CFO) and Channel Distortion Using Two Repeated Training Sequences proposed in section V. II. MIMO OFDM SYSTEM MODEL Multiple input multiple output (MIMO) is the use of multiple antennas at both the transmitter and receiver to improve performance of the communication



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system. MIMO technology has gained lots of attention in wireless communication systems because it offers significant increases in data throughput and link range without additional bandwidth. The combination of Multiple Input Multiple Output (MIMO) with Orthogonal Frequency Division Multiplexing (OFDM) is best technology for fourth generation (4G) wireless communications. However, the high data rate performance of the MIMO OFDM system is very sensitive to Carrier Frequency Off Offset (CFO) which introduces Inter Carrier Interference (ICI).

Consequently, Carrier Frequency Offset (CFO) and Channel Distortion estimation plays a key role in MIMO OFDM systems. MIMO-OFDM system is a combination of MIMO and OFDM techniques to achieve the high spectral efficiency and increases data rate. MIMO-OFDM system transmits independent modulated signals from multiple antennas simultaneously [4]. At the receiver receives the input data, and after demodulate the data, MIMO decoding on each of sub channels extracts the data from all the transmitted antenna data on all the sub channels. From the figure 1 Nt is the number of transmitter antennas and Nr is the number of receiver antennas. The MIMO OFDM system transmitter has Nt parallel transmission paths which are very similar to the single antenna OFDM system. Each and every branch channel perform serial to parallel conversion, N-point IFFT (Inverse Fast Fourier Transform), pilot insertion and cyclic prefix (CP) or cyclic extension before the final transmission. The channel encoder and modulation can also be done each branch, but not necessary implemented jointly over each Nt branches. In MIMO OFDM system Nt different signals are transmitted simultaneously over the channel paths (Nt × Nr) and each received signal is a combination of transmitted signal and distortion noise [5]. Firstly, the receiver must estimate and correct the possible symbol errors and frequency offsets. At the receiver Cyclic Prefix (CP) is removed and N-point Fast Fourier Transform is performed per receiver branch. In this project the estimation of channel distortion and CFO is based on the single carrier processing that implies MIMO detection has to be done per OFDM

subcarrier. Therefore, the received signals of subcarrier k are routed to the kth MIMO decoder to recover all the Nt transmitted data signals on the subcarrier. After the transmitted symbol the transmission (TX) antenna is combined and then outputted for the subsequent operations like demodulation and decoding. III. CARRIER FREQUENCY OFFSET (CFO)

TWO ALGORITHMS FOR MIMO OFDM SYSTEMS

This section describes about Carrier Frequency Offset estimation two algorithms for multiple inputs multiple output Orthogonal Frequency Division Multiplexing (OFDM) systems. Mody etal. proposed a method which uses training sequences for CFO and Chanel Distortion estimation in OFDM system. After performing the Fast Fourier Transform (FFT) transform of the training sequences at receiver, CFO estimation is achieved in frequency domain. Yao and Giannakis developed a low-complexity blind CFO estimator for OFDM systems, which can be applied to CFO estimation in MIMO OFDM systems. For estimation of Carrier Frequency Offset (CFO) each antenna must be assigned a training sequence. The training sequences are composed using repeated pseudo-noise (PN) sequence. Thus interference of inter transmit antenna is eliminated. The training sequences occupy different subcarriers in the same OFDM symbol interval from different transmit antennas. The structure of the training sequences is shown in below figure [14]. The length of the training sequence is Nt and that of pseudo-noise (PN) sequence is Np. Let M is the [Nt/Np] which is integer part of the Nt/Np. The last PN sequence in the training sequence may be incomplete [15]. The received signal on the ith receive antenna is

Figure 2: The structure of training sequences in transmits

antennas



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The training sequence contains M (a positive integer) several identical PN sequences. At the transmitter the first PN sequence is generated through reducing the FFT length to Np. at the transmitter, the number “M” is important and should be appropriately selected. The synchronization is performed at the receiver and then the received training sequence can be found [13, 16]. A. Carrier Frequency Offset (CFO) Acquisition Algorithm On the same antenna, the corresponding samples from different PN sequences in a received training sequence have some phase difference which is caused by CFO and can be used to estimate CFO. When there is no channel fading and noise the relationship between corresponding samples from different PN sequences in a received training sequence on the same antenna is given by

B. Carrier Frequency Offset (CFO) Tracking Algorithm

IV. PROPOSED JOINT ESTIMATION OF

CARRIER FREQUENCY OFFSET (CFO) AND CHANNEL DISTORTION

This section describes a new method that is joint estimation of Carrier Frequency Offset (CFO) and Channel Distortion for MIMO OFDM systems. In recent years MIMO OFDM systems got lots of attention due to its low power consumption and low implementation cost. However some mismatches occur at OFDM receiver can seriously degrade the system performance, such as carrier frequency offset (CFO) and channel distortion. Chanel distortion accurse due to the amplitude and phase mismatches of the local oscillator. And CFO is due to the mismatch of carrier frequency at the transmitter and receiver. And CFO occurs due to the difference between the references frequencies of local oscillators at the receiver and transmitter. Therefore CFO destroys the orthogonally between different subcarriers causes Inter Carrier Interference (ICI). The ICI causes degrade the system performance severely if not properly compensated [17]. And one more degrade parameter of OFDM system is channel distortion. Therefore, practical OFDM systems need CFO and channel distortion to be compensated with sufficient accuracy. The figure 1 shows the mathematical signal model of MIMO OFDM system.



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V. SIMULATION RESULTS AND

DISCUSSIONS This section describes the simulation results of the proposed estimation methods for MIMO OFDM system. The parameters used in simulation are shown in table I.

The performance of the proposed method joint estimation of Carrier Frequency Offset (CFO) and Channel Distortion form MIMO OFDM System is evaluated through simulations. We considered the channel length L= 64 and length of the Cyclic Prefix (CP) is L-1= 63, channel noise considered as Additive White Gaussian Noise (AWGN) in both cases. And total length of the training sequence is 64 as of the same poly-phase sequence are transmitted for CFO and Channel Estimation. The simulations results are shown in two cases are

(1) Simulation results of Channel Distortion for MIMO OFDM System In Case (A) 3 transmit and 2 receiver antennas are used. The performance results are shown Mean



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Squared Error (MSE) of Channel Distortion and Carrier Frequency Offset (CFO). The Mean Squared Error (MSE) is defined as the average error within an OFDM block. If the (OFDM) block consists of two repeated training sequences the joint estimation can be achieved by using equations (24) and (25). The figure 3(a) and 3(b) shows the performance of the channel distortion estimation using the proposed methods for both Case (A) and Case (B). From these figures we can found that proposed estimation methods provide a good performance, and they are robust for different types of mismatch parameters. Form the figures 3(a) and 3(b) we can see the proposed estimation curve described in section (4.1) and two step joint estimation performance curve described in Section (4.2). And also found that the proposed methods outperform the Channel Distortion- CFO method in both cases.

Figure 3: Mean Squared Error (MSE) of Channel Distortion in

Case (A) and Case (B)

(2). Simulation results of Carrier Frequency Offset (CFO) for MIMO OFDM system The proposed estimation method using training sequences described in section 4.1 using training sequences as “Proposed (Sec 4.1)” in the simulation results. And the joint estimation using two training sequences was discussed in section 4.2. This method denote in simulation results as a “Two-step (Sec 4.2)”. From the equation (8), the vector signal due to Carrier Frequency Offset (CFO) is achieved. If the OFDM block consists of two repeated training sequences, the joint estimation can be achieved by using equations (24) and (25).

Figure 4: Mean Squared Error (MSE) of Carrier Frequency

Offset in Case (A) and Case (B) The figures 4(a) and 4(b) shows the Mean Square Error (MSE) of the estimation of Carrier Frequency Offset (CFO). From the above figures we can see that our proposed methods provide a good performance for estimation of Carrier Frequency Offset (CFO). Note that Mean Square Error (MSE) of Case (B) is larger than the Mean Square Error (MSE) of Case (A)



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since there are more transmit antennas and there are more channels in the estimation. The Mean Squared Error (MSE) is defined as the average error within an OFDM block. In Case (A) 4 transmit and 1 receiver antennas are used. And in Case (B) 4 transmit and 1 receiver antennas are used for comparison. In Case (A) the channel distortion- CFO joint estimation method performs very well when the Signal to Noise Ratio (SNR) is low. In Case (B) the proposed methods are significantly better than the channel distortion- CFO method. CONCLUSION In this paper, proposed new methods for the joint estimation of Carrier Frequency Offset (CFO) and Channel Distortion for MIMO OFDM systems using training sequences. The Carrier Frequency Offset (CFO) acquisition and tracking two algorithms are proposed for MIMO OFDM systems to improve the estimation accuracy. When only one OFDM block is available for training, the first method is able to give an accurate estimation of the Carrier Frequency Offset (CFO) and Channel Distortion. When two repeated training sequences are available in OFDM block, low complexity two step approach is proposed to solve the joint estimation problem. Simulation results are showed that the Mean Squared Error (MSE) of Carrier Frequency Offset (CFO) and Mean Squared Error (MSE) of Channel distortion in both proposed method and two step approach method. The simulation results are showed in two cases for comparison. REFERENCES [1]. P. H. Moose, “A technique for orthogonal frequency division

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