A Novel Hybrid OFDM Technique for 5G Onur Dursun Tören, Emre Ayduslu, Yücel AydÕn and Ali Özen Nuh Naci Yazgan University - HARGEM Department of Electrical and Electronics Engineering, 38010 Kayseri, Turkey. Email: toren_onur@hotmail.com, emreayduslu@gmail.com, yucelaydin50@hotmail.com, aozen@nny.edu.tr interference (ISI) affected multipath channels. These channels often experience strong frequency selective fading. OFDM has been chosen for current communication systems like LTE [5], Wireless LAN IEEE 802.11a [6] or DAB, DVB-T [7]. The high data rate payload is multiplexed over a set of sub-carriers that are orthogonal to one another. In OFDM, the symbol period is significantly increased and with the use of suitable cyclic extension, the received data sequence (in the frequency domain) is not affected by the time dispersive nature (ISI) of the channel. However, it is known that OFDM, which is used in existing LTE systems for asynchronous network and wireless systems expected to become widespread in the future, is not appropriate. Taken place in standards related to many different Wired and wireless systems and widely used with broadband systems OFDM method cannot meet the needs of the next generation systems in every situation; the search for alternative waveform methods has gained speed. For this reason, it is considered that the OFDM technique will not be sufficient for 5G and later for the waveform, which is effective in selecting several subcomponents of communication systems [8]. In previous 5G studies, the drawbacks of the OFDM method for new designs have been taken as a basis, but a waveform, which can be regarded as the best in terms of overall performance criteria with clear and superiority over the OFDM method, has not been yet developed. Each of the existing waveform techniques has various positive and negative aspects, and therefore the search for the new waveform method is ongoing. One of the design modifiers may need to be traded-off during the healing of one of the other modifiers. Efforts are being made to optimize the most appropriate design in this during trade-off. The current waveforms proposed for 5G are generally compared with the OFDM technique [9]. The new waveforms designed for the upcoming 5G can now be classified as Zero-Tail OFDM (ZT OFDM) [10], ZT Discrete Fourier Transform (DFT) spread OFDM (ZT DFT-s OFDM) [11], Unique Word OFDM (UW OFDM) method [12], Filter Bank Multi Carrier (FBMC) method [13], Universal Filtered Multi Carrier (UFMC) method [14], Filtered OFDM (F-OFDM) [15] method and Generalized Frequency Division Multiplexing (GFDM) [16] method. In this study, a new hybrid OFDM (H-OFDM) method is proposed to improve the performance of the conventional OFDM method and unique word OFDM (UW OFDM) technique from 5G candidate waveforms. In order to compare the proposed H-OFDM with the conventional OFDM system, computer simulations are Abstract—A novel hybrid orthogonal frequency division multiplexing (H-OFDM) technique, for 5G candidate waveforms, has been proposed to improve the performance of conventional OFDM systems in this paper. In H-OFDM system instead of conventional cyclic prefixes (CPs) it is used hybrid CP as a guard interval. The hybrid CP consists of zero tail (ZT), unique word (UW) and CP. Computer simulations have been performed to show the performance of the proposed system in stationary and non-stationary frequency selective Rayleigh fading channels. The obtained simulation results using IEEE 802.16 physical layer specifications have demonstrated that the proposed H-OFDM method has considerably better performance and Doppler shift tracking than conventional OFDM. Keywords—Hybrid Waveform Design. CP; ZT-OFDM; UW-OFDM; 5G; I. INTRODUCTION Communication technologies have become an integral part of our society, having an extreme socio-economic impact, and enriching our daily lives with an excess of services from media entertainment (e.g. video) to more sensitive and safety-critical applications (e.g. e-commerce, e-Health, first responder services, etc.). If analysts’ predictions are correct, just about every physical object we see (e.g. clothes, cars, trains, buses, etc.) will also be connected to the networks by the end of the decade, called Internet of Things (IoT) [1]. Due to too much data traffic request the International Telecommunication Union (ITU) has described the conditions for international mobile communication in 2020 and beyond [2]. These are aimed at data rates of 20 Gbps, user data rates of 100 Mbps to 1 Gbps, and a minimum latency of less than 1 ms. Current radio access technologies such as Long Term Evolution (LTE) and advanced long-term evolution (LTEAdvanced) have problems such as incompatibility constraints and internal constraints to meet ITU requirements [2]. The industry and academia are exploring new methods for 5th Generation (5G) radio access technology that will remove previous generation radio access technologies [3]. Additionally, the number of terminals will increase exponentially due to new technologies such as Machine to Machine (M2M), Vehicular to Vehicular (V2V) and Device to Device (D2D) that will come with 5G and later technologies [4]. Communication technologies are being developed to achieve ever high date rates over power and band limited radio channels. Orthogonal frequency division multiplexing (OFDM) has appeared as a strong contender for use with inter symbol 978-1-5090-3982-1/17/$31.00 ©2017 IEEE 195 TSP 2017 executed on stationary and non-stationary frequency selective Rayleigh fading channels. From the obtained results, it is seen that the proposed H-OFDM system has better performance than the conventional OFDM system in both stationary and nonstationary channels. The rest of the paper is organized as follows: the Unique Word OFDM system model used in simulations is summarized in Chapter 2. The proposed H-OFDM-FDE structure is described in detail in Chapter 3. The performed computer simulations have been introduced in the fourth section. The obtained results by taking into account computer simulation results are given in the last section. improving the performance of conventional OFDM system. The hybrid CP (H-CP) consists of zero tail, unique word and conventional CP as shown in Figure 2. II. UNIQUE WORD OFDM In the proposed H-CP, conventional CP length is of channel impulse response length, UW length is of half-length of CP and the rest of the CP is assigned ZT, filled with zero. CAZAC sequence, given in IEEE 802.16 standard, has been used as a unique word in this proposed technique. Since the UW is deterministic sequence, it can be optimally designed for particular needs like synchronization and/or channel estimation purposes at the receiver side. Additionally, in UW-OFDM the guard interval is part of the FFT interval, whereas this is not the case for CP-OFDM which improves the bit error ratio (BER) performance [17]. However, Zero Tail (ZT) OFDM has the superior spectral density of the generated waveform than CPOFDM [10]. Therefore, in this study, due to the conveniences of ZT and the advantages of UW, a new H-CP is designed to improve the performance of the conventional OFDM method and UW-OFDM technique from 5G candidate waveforms. The block diagram of the transmitter and the receiver structure of the proposed H-OFDM system using the frequency domain channel equalizer (FDE) is given in Figure 3. OFDM Symbol H-CP Data 1 CP1 UW Data 1 UW CP2 Data 2 Data 2 H-CP Unique Word Data 2 CP2 Serial UW FEC Input Coding Fig. 1. Transmit symbol structures for CP-OFDM and UW-OFDM. CP I-Q Mapping IFFT H-CP Adding ISI Channel Some key differences between a UW and a CP based OFDM system can be pointed out: 1. The UW lies inside the Fast Fourier Transform (FFT) window, while the CP lies outside the FFT interval. 2. The CP is based on the transmitted data. Since the OFDM data symbol varies from symbol to symbol the CP is observed to be random. 3. The UW is deterministic and therefore the same for all OFDM symbols. Key characteristic of a Unique Word are that it has good periodic correlation properties, and its symbols have constant amplitude. Ideally, the sequence is constant amplitude zero auto-correlation (CAZAC) sequence. Unique Words could be used for channel; timing and carrier offset estimation for OFDM system [18]. H-CP Fig. 2. The proposed H-OFDM system symbol structure. OFDM Symbol CP1 H-CP Zero Tail Instead of CP, which is a random sequence in the CP-OFDM technique, a non-random sequence, unique-word (UW), is used in the UW OFDM method [17]. Since UW is known sequences, it can be used for time-frequency alignment and channel estimation. Compared to the CP-OFDM technique, out-of-band propagation is less in the UW-OFDM scheme. However, computational complexity is greater in UW-OFDM [9]. Figure 1 illustrates the differences between the conventional CP-OFDM and the UW-OFDM transmitted symbol structures. OFDM Symbol Data 1 OFDM Symbol AWGN Serial FEC DeOutput Coding I-Q De Mapping FDE FFT H-CP Removing Fig. 3. Block diagram of the proposed H-OFDM system transmitter and receiver structure. Figure 3 shows the proposed technique block diagram’s basic components for the receiver and the transmitter in multi carrier communications, where it is used Reed Solomon and convolutional coding for forward error correction (FEC) coding, and soft output Viterbi decoding for the FEC decoding. After the data coming as serially from the source are coded by the (255, 239, GF 28) Reed-Solomon coding for the outer code [19], block interleaved [19] and then coded by the binary convolution code (CC) with the rate of 1/2 as an inner code [19]. The output of the FEC encoder is divided into groups by III. THE PROPOSED H-OFDM SYSTEM The proposed method, inspired by [18], considers the hybrid cyclic prefix instead of conventional CP as a guard interval, 196 Conventional OFDM-FDE LMS Channel Estimation 1E-2 Proposed H-OFDM-FDE LMS Channel Estimation 1E-3 OFDM-FDE RLS Ch. Est. 1E-4 Reference [18] Channel Known 1E-5 1E-6 0 5 10 OFDM-FDE Ch. Known Proposed M. RLS Ch. Est. Proposed H-OFDM-FDE Channel Known AWGN Channel 15 20 25 30 35 40 Proposed M. Ch. Known Proposed M. RLS Ch. Est. Proposed M. LMS Ch. Est. OFDM-Coded Ch. Konown OFDM-Coded RLS Ch. Est. OFDM-Coded LMS Ch. Est Ref. [18] Ch. Known OFDM-Uncoded AWGN 45 SNR (dB) Fig. 4. Comparison of the coded BER-SNR performances of conventional OFDM, Reference [18] and proposed H-OFDM systems using 4-QAM modulation. It can be seen from the Figure 4 the coded BER performance obtained using the LMS channel estimation in conventional OFDM-FDE converges to lower 1E-2 BER value but the obtained result is not of significance. It is observed that the proposed H-OFDM-FDE, with LMS channel estimation, performs better than the conventional OFDM-FDE and it also converges to lower 5E-4 BER floor. The BER performance of the proposed H-OFDM-FDE, with RLS channel estimation, gets better than the performance of the conventional OFDMFDE, Reference [18] and converges to the performance of the case of channel known. Additionally, while the performance of the conventional OFDM-FDE, with RLS channel estimation, converges to error floor, the performance of the proposed method removes the error floor. The un-coded BER versus SNR performances of the conventional OFDM-FDE, Reference [18] and the proposed H-OFDM-FDE equalizers are given in Figure 5 for 4-QAM modulation. IV. COMPUTER SIMULATION RESULTS The computer simulation works have composed of two phases. In the first phase works are performed using the simulated stationary communication channel. In the second phase works are executed employing non-stationary communication channel. Bit error rate (BER) performances are obtained at the output of error correcting decoder for both the simulated stationary communication channel and the non-stationary communication channel with frequency domain channel equalizer (FDE). A. Simulation Results of Stationary Channel {0.227, 0.46, 0.688, 0.46, 0.227} Simulated Proakis Channel Profile, 4-QAM, FDE, Un-Coded 1E-1 Conventional OFDM-FDE LMS Channel Estimation 1E-2 BER In this first phase, simulation results are exhibited to verify the performance of the proposed H-OFDM method in simulated stationary frequency selective Rayleigh fading channels. The proposed technique is compared with conventional OFDM and Reference [18]. The simulation studies are executed using the physical layer specifications of IEEE 802.16 via 1000 independent Monte Carlo type iterations employing 20 OFDM data blocks for the 4-QAM modulation. In this paper, a five taps channel profile with average coefficient amplitudes given by (0.227, 0.46, 0.688, 0.46, 0.227), which is defined by Proakis, is employed [20]. Simulation studies have been done by taking the step size parameter of the Least Mean Squares (LMS) algorithm is 0.045 and the forgetting factor parameter of the Recursive Least Squares (RLS) algorithm is 0.985 employed in estimation of the channel coefficients. The coded BER versus SNR performances of the conventional OFDM-FDE, Reference [18] and the proposed H-OFDM-FDE equalizers are given in Figure 4 for 4-QAM modulation. {0.227, 0.46, 0.688, 0.46, 0.227} Simulated Proakis Channel Profile, 4-QAM, FDE, Coded 1E-1 BER means of I-Q mapping depending on the number of bits to be sent by a sub-carrier and is modulated with one of the desired modulation types (BPSK, QPSK, 16-QAM, 64-QAM and 256QAM). After taken the inverse fast Fourier transform of the I-Q matched data and added the proposed H-CP, OFDM symbols are generated. The obtained OFDM symbols are transmitted over a multipath channel and corrupted by additive white Gaussian noise (AWGN). In the receiver, the H-CP of the received data is removed and equalized with frequency domain channel equalizer after the FFT process. The equalized datas are demodulated by the I-Q de-mapping block. The demodulated datas are decoded by inner decoder, deinterleaved and decoded again by the outer decoder. ReedSolomon decoder and soft output Viterbi algorithm (SOVA) are used together in FEC decoding. Finally, output data is obtained at the output of FEC decoding block and then any desired performance comparisons are also executed. Proposed H-OFDM-FDE LMS Channel Estimation 1E-3 OFDM-FDE RLS Ch. Est. 1E-4 1E-6 0 5 10 15 20 25 30 35 Proposed M. LMS Ch. Est. OFDM-Uncoded Ch. Known OFDM-Uncoded RLS Ch. Est. Ref. [18] Uncoded Ch. Known Reference [18] Channel Known Proposed M. RLS Ch. Est. AWGN Channel Proposed M. RLS Ch. Est. OFDM-Uncoded LMS Ch. Est. Proposed H-OFDM-FDE Channel Known 1E-5 Proposed M. Ch. Known 40 OFDM-Uncoded AWGN 45 SNR (dB) Fig. 5. Comparison of the un-coded BER-SNR performances of conventional OFDM,Reference [18] and proposed H-OFDM systems using 4-QAM modulation. When the un-coded BER-SNR performances belong to the 4-QAM modulation is investigated in Figure 5, similar performances are also obtained in coded BER performances in 197 Figure 4. The performance differences are protected between the proposed method and conventional OFDM-FDE and Reference [18]. Because only coding is not used, SNR values have changed. In this second phase of the work, simulations are also obtained for 4-QAM modulated systems employing 20 OFDM data blocks with IEEE 802.16 physical layer properties in 5.2 GHz carrier frequency over 1000 independent Monte Carlo loops for non-stationary channels. It is quite common to use an RMS delay spread of 30-90 ns with Rayleigh channel delay profile, for this paper we have used a more demanding five tap channel profile with average coefficient amplitudes given by (0.227, 0.46, 0.688, 0.46, 0.227), which is defined by Proakis [20] and corresponds to an RMS delay spread of approximately 50 ns for our system configuration. Simulation studies have been done by taking the step size parameter of the LMS algorithm is 0.085 and the forgetting factor parameter of the RLS algorithm is 0.85 used for estimation of the channel coefficients in channel tracking. After the channel is estimated, equalization process is executed again in the frequency domain. The maximum Doppler frequency values that will occur at various speeds and carrier frequencies in a receiver moving at a constant speed are given in Table 1. TABLE I. 1E-1 1800 2400 8.333 11.111 33.333 44.444 83.333 111.111 166.666 222.222 200.000 266.666 400.000 533.333 500.000 666.666 666.666 888.888 833.333 1111.111 1E-6 Proposed M. LMS Ch. Tr. Proposed H-OFDM Coded RLS Ch. Tracking 0 5 10 15 20 25 30 Proposed H-OFDM Un-Coded RLS Ch. Tracking 35 40 45 OFDM-Coded LMS Ch. Tr. OFDM-Uncoded LMS Ch. Tr. Ref. [18] Coded RLS Ch. Est. SNR (dB) Fig. 6. Comparison of Doppler tracking coded and un-coded BER-SNR performances of conventional OFDM, Ref. [18] and proposed H-OFDM systems using 4-QAM modulation in case of a Doppler frequency of 240 Hz. In case of Doppler frequency is of 240.740 Hz (mobile vehicle speed is of 50 km/h), when the obtained coded and uncoded BER performances of the conventional OFDM, Reference [18] and proposed method are examined in Figure 6, the coded and un-coded performances of the proposed HOFDM-FDE, with RLS channel tracking, outperform the performances of conventional OFDM-FDE and Reference [18]. Additionally, as can be seen from the Figure 6 coded and un-coded BER performances of both techniques remove the error floor. The coded and un-coded performances of the proposed H-OFDM-FDE, with LMS channel tracking, outperform the performances of conventional OFDM-FDE. Moreover, as can be observed from the Figure 6 coded and uncoded BER performances of both techniques, with LMS channel tracking, converge the error floor. 5200 24.074 96.296 240.740 481.481 577.777 1155.555 1444.444 1925.925 2407.407 In case of the mobile vehicle speed is 50 km/h (Doppler frequency is 240.740 Hz) in Figure 6, the mobile vehicle speed is 120 km/h (Doppler frequency is 577.777 Hz) in Figure 7, and the mobile vehicle speed is 240 km/h (Doppler frequency 1155.555 Hz) in Figure 8, coded and un-coded BER-SNR performance comparison between the proposed H-OFDMFDE, Reference [18] and the conventional OFDM-FDE system are given for belong to the channel tracking. Proposed M. LMS Ch. Tr. Conventional OFDM Coded RLS Ch. Tr. 1E-5 {0.227, 0.46, 0.688, 0.46, 0.227} Simulated Proakis Channel Profile, 4-QAM, FDE, V. S. = 120 km/h 1E-1 Proposed H-OFDM LMS Ch. Tracking Conventional OFDM LMS Ch. Tracking Proposed M. RLS Ch. Tr. Proposed M. RLS Ch. Tr. OFDM-Coded RLS Ch. Tr. 1E-2 BER Vehicle Speed [km/h] 4.166 16.666 41.666 83.333 100.000 200.000 250.000 333.333 416.666 Proposed M. RLS Ch. Tr. OFDM-Uncoded RLS Ch. Tr. 1E-3 Reference [18] Coded RLS Ch. Tracking Carrier Frequency, MHz 5 20 50 100 120 240 300 400 500 Conventional OFDM LMS Ch. Tracking Proposed M. RLS Ch. Tr. OFDM-Coded RLS Ch. Tr. 1E-4 THE MAXIMUM DOPPLER FREQUENCY VALUES IN VARIOUS CARRIER FREQUENCY AND SPEEDS. 900 Proposed H-OFDM LMS Ch. Tracking 1E-2 BER B. Simulation Results of Non-Stationary Channel {0.227, 0.46, 0.688, 0.46, 0.227} Simulated Proakis Channel Profile, 4-QAM, FDE, V. S. = 50 km/h OFDM-Uncoded RLS Ch. Tr. 1E-3 Proposed M. LMS Ch. Tr. Proposed H-OFDM Un-Coded RLS Ch. Tracking 1E-4 Reference [18] Coded RLS Ch. Tracking Proposed H-OFDM Coded RLS Ch. Tracking OFDM-Coded LMS Ch. Tr. Conventional OFDM Coded RLS Ch. Tr. 1E-5 0 5 10 15 20 25 Proposed M. LMS Ch. Tr. 30 OFDM-Uncoded LMS Ch. Tr. 35 40 45 Ref. [18] RLS Ch. Est. SNR (dB) Fig. 7. Comparison of Doppler tracking coded and un-coded BER-SNR performances of conventional OFDM, Ref. [18] and proposed H-OFDM systems using 4-QAM modulation in case of a Doppler frequency of 577 Hz. In case of Doppler frequency is of 577.777 Hz (mobile vehicle speed is of 120 km/h), when the obtained coded and un-coded BER performances of the conventional OFDM-FDE, Reference [18] and proposed technique are observed in Figure 7, the coded and un-coded performances of the proposed HOFDM-FDE, with RLS channel tracking, outperform the 198 performances of conventional OFDM-FDE and Reference [18]. However, the obtained performances of channel tracking start to be varying since the all methods produce error floor. {0.227, 0.46, 0.688, 0.46, 0.227} Simulated Proakis Channel Profile, 4-QAM, FDE, V. S. = 240 km/h 3E-1 Proposed H-OFDM LMS Ch. Tracking 1E-1 Conventional OFDM LMS Ch. Tracking BER [1] [2] Proposed M. RLS Ch. Tr. Proposed M. RLS Ch. Tr. [3] OFDM-Coded RLS Ch. Tr. 3E-2 OFDM-Uncoded RLS Ch. Tr. 1E-2 Conventional OFDM Un-Coded RLS Ch. Tr. Proposed H-OFDM Un-Coded RLS Ch. Tracking 3E-3 1E-3 Conventional OFDM Coded RLS Ch. Tr. Reference [18] Coded RLS Ch. Tracking 3E-4 1E-4 REFERENCES Proposed H-OFDM Coded RLS Ch. Tracking 0 5 10 15 20 25 30 35 [4] Proposed M. LMS Ch. Tr. Proposed M. LMS Ch. Tr. [5] OFDM-Coded LMS Ch. Tr. OFDM-Uncoded LMS Ch. Tr. 40 45 Ref. [18] Coded RLS Ch. Est. [6] SNR (dB) Fig. 8. Comparison of Doppler tracking coded and un-coded BER-SNR performances of conventional OFDM, Ref. [18] and proposed H-OFDM systems using 4-QAM modulation in case of a Doppler frequency of 1155 Hz. [7] In case of Doppler frequency is of 1155.555 Hz (mobile vehicle speed is of 240 km/h), when the obtained coded and un-coded BER performances of the conventional OFDM-FDE, Reference [18] and proposed method are examined in Figure 8, similar performances are also obtained for 4-QAM. However, the obtained coded and un-coded BER performances are worse than the performances in the case of Doppler frequency is of 240 Hz and 577 Hz. [8] [9] [10] V. CONCLUSION A new Hybrid OFDM (H-OFDM) system is proposed for 5G, in order to improve the performance of conventional OFDM system in this study. Hybrid cyclic prefix (H-CP), consisting of zero tail, unique word and conventional CP, is employed in the proposed technique. It has been shown that a combination of conventional OFDM and the proposed H-CP method provides an effective and robust way for adaptive channel equalization and channel tracking for 5G. The proposed technique has been applied to the frequency domain channel equalization of a multi carrier IEEE 802.16 radio standard in stationary and non-stationary frequency selective Rayleigh fading channels. The performance improvement by the proposed technique is very significant. Thus, the conventional OFDM has become with a high performance waveform technique for 5G. The results of this study show that the proposed H-OFDM based on H-CP is also shown to be very suitable for high speed channel tracking and offers a very low complexity alternative for high performance applications for 5G and beyond. [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] 199 J. Rodriguez, Fundamentals of 5G Mobile Networks, First Edition, John Wiley and Sons Ltd., Portugal, 2015. 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