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				<title level="a" type="main">A Review on Orthogonal Time Frequency Space Modulation</title>
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							<persName><forename type="first">Suresh</forename><surname>Kumar</surname></persName>
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								<orgName type="institution" key="instit1">University Institute of Engineering &amp; Technology</orgName>
								<orgName type="institution" key="instit2">Maharshi Dayanand University</orgName>
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									<settlement>Rohtak</settlement>
									<region>Haryana</region>
									<country key="IN">India</country>
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							<persName><forename type="first">Seema</forename><surname>Deshwal</surname></persName>
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								<orgName type="institution" key="instit1">University Institute of Engineering &amp; Technology</orgName>
								<orgName type="institution" key="instit2">Maharshi Dayanand University</orgName>
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									<settlement>Rohtak</settlement>
									<region>Haryana</region>
									<country key="IN">India</country>
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						<title level="a" type="main">A Review on Orthogonal Time Frequency Space Modulation</title>
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					<term>OTFS modulation</term>
					<term>delay-Doppler domain</term>
					<term>OFDM</term>
					<term>Future wireless network</term>
					<term>BER</term>
					<term>PAPR</term>
					<term>SNR</term>
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<div xmlns="http://www.tei-c.org/ns/1.0"><p>Orthogonal Time Frequency Space (OTFS) modulation scheme is an advanced modulation scheme having two-dimension widely used in futuristic wireless networks due to its high data rate, more flexibility and higher reliability. In high mobility cases OTFS provide better performance of connectivity. OTFS modulation operates in delay -Doppler domain while OFDM operates in time frequency domain. This paper provides an overview of OTFS operating in delay Doppler domain with its advantage and disadvantage. This modulation scheme has numerous applications in next generation network such as drone communication, communication in hilly area, high speed mobility such as railway communication and vehicle to vehicle communication. This paper presents the latest developments in OTFS modulation in a simpler and easy way. Performance comparison of OTFS with other modulations schemes has also been presented in the terms of evaluation parameters like: BER, PAPR and SNR.</p></div>
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<div xmlns="http://www.tei-c.org/ns/1.0"><head n="1.">Introduction</head><p>In future we are expecting wireless networks to meet the requirement of higher mobility to support user equipment. It is expected to have the speed up to 300Km/hr for automobile connections and up to 550Km/hr in railways network connection applications. New emerging high-speed vehicle scenarios such as high-speed railway communication, drone communication, communication in hilly regions, vehicle to vehicle communication will be engineered based on OTFS <ref type="bibr" target="#b0">[1]</ref>. In wireless communications, due to the hostile channel variation at high carrier frequencies in high mobility scenarios is extremely challenging. Relying scheme will offer certain degree of robustness against variations in channels, which may be coherently adaptive or non-coherent in nature for detection <ref type="bibr" target="#b1">[2]</ref>. For high mobility communication of future wireless network research attention has been increased and resulted in design of modified modulation waveform and schemes.</p><p>High-mobility communications mainly suffer from severe Doppler spreads operating at high carrier frequencies, which is mainly due to higher relative motion existence between the Receiver, Transmitter, and scatterers. Although, Orthogonal Frequency Division Multiplexing (OFDM) modulation suffers in high -mobility scenarios, which found wide application in 4G and 5G cellular system.</p><p>In a digital multicarrier modulation technique that consists on sending multiple subcarriers orthogonal to each other with overlapping spectra in the frequency domain. They carry data in parallel and are closely spaced. OFDM is resilient to selective fading, interference, and multipath effects due to low bit rate in each of its carrier. OFDM also have several challenges such as high Peak to Average Power Ratio (PAPR), sensitive to drift with carrier offset, and hence not found suitable for selective fading channels. Currently a modified modulation scheme executed in two dimension and named as OTFS has been introduced in order to support the increased mobility communications <ref type="bibr" target="#b2">[3]</ref>.</p><p>OTFS modulation uses modulation in Delay-Doppler (DD) domain rather in Time -Frequency (TF) domain as done in OFDM. To support reliable communication OTFS provides strong DD resilience. In the DD domain OTFS modulation transforms a time-variant channel into a 2Dquasi-time-invariant channel. OTFS seems to have full potential for challenging fundamental research to overcome the problems in channel estimation together for detection, application of multi-antenna system and multiuser designs.</p></div>
<div xmlns="http://www.tei-c.org/ns/1.0"><head n="2.">OTFS</head><p>OTFS is a modulation technique in two-dimension, which operates in DD domain. OTFS gives an output as non-fading, time independent channel on getting an input of fading time variant channel. Basic diagram of wireless network consists of transmitter and receiver, with multipath fading is shown in given figure1. Here 𝘩(𝜏, 𝜐)= represents function for the channel spreading [it represents Fourier-transform of timevariant impulse response𝘩(𝜏, 𝚝)] <ref type="bibr" target="#b3">[4]</ref>. Where 𝜏 is for delay and 𝜐 is for Doppler shift .</p></div>
<div xmlns="http://www.tei-c.org/ns/1.0"><head n="2.1.">OTFS Transmitter and Receiver</head><p>Heisenberg transform which can be parameterized by function 𝘩(𝜏, 𝜐), is used for mapping the transmitted signal into received signal. OTFS modulation consists of a cascade of two 2-dimensional transforms for the Transmitter and Receiver. Basic block diagram for OTFS is shown in figure <ref type="figure" target="#fig_1">2</ref>. </p><p>In equation ( <ref type="formula" target="#formula_0">2</ref> </p><p>The OTFS transform, combination of windowing and inverse SFFT is described further as under:</p><p>Subsequently, it is shown in the figure <ref type="figure" target="#fig_1">2</ref> that Heisenberg transform carry out the function to generate time domain signal s(𝘵) from a time frequency signal as shown:</p><formula xml:id="formula_2">𝑠(𝑡) = 𝑌(𝑛, 𝑚)𝑔ₜ(𝑡 − 𝑛𝑇)𝑒 ( ) ̸ / ̸ /<label>(4)</label></formula><p>Where 𝑌 = 𝑊ₜ * 𝑆𝐹𝐹𝑇¯¹(𝑦),Whereas at transmitter 𝑊(t) represents the time -frequency windowing function. It can be described as Heisenberg operator having the parameter 𝑋[𝑛, 𝑚] applied to basic pulse of transmission 𝑔ₜ(𝘵). It is also noticed that transmitted and received pulse follow the bi-orthogonality condition and is given by:</p><formula xml:id="formula_3">𝑔ₜ(𝑡)𝑔ᵣ(𝑡 − 𝑛𝑇)𝑒 ( ) 𝑑𝑡 = 𝛿(𝑚)𝛿(𝑛)<label>(5)</label></formula><p>Thus, it is seen that received signal is the result of cascading of two Heisenberg operators operating on basic pulse. One of them is OTFS transform without modulation and the second is expressed due to interaction with channel. The parameter ℎ1 and ℎ2 are the cascading of two Heisenberg operators and used here to represent the two original operators in the form of twisted convolution.</p><formula xml:id="formula_4">ℎ₁(𝜏, 𝜐) * 𝜎ℎ₂(𝜏, 𝜐) = ℎ₂(𝜏ʹ, 𝜐ʹ) ℎ₁(𝜏 − 𝜏ʹ, 𝜐 − 𝜐ʹ)𝑒 ʹ( ) 𝑑𝜏ʹ𝑑𝜐ʹ<label>(6)</label></formula><p>Therefore, the received signal is given as</p><formula xml:id="formula_5">𝑟(𝑡) = 𝑓 (𝜏, 𝜐)𝑒 ( ) 𝑔ₜ(𝑡 − 𝜏)𝑑𝜏ʹ𝑑𝜐ʹ<label>(7)</label></formula><p>In equation <ref type="bibr" target="#b6">(7)</ref>, 𝑓(𝜏, 𝜐) is called the Impulse response resulted from the combined transform.</p><formula xml:id="formula_6">𝑓(𝜏, 𝜐) = ℎ(𝜏, 𝜐) * 𝜎𝑌[𝑛. 𝑚] = 𝑌[𝑛, 𝑚]ℎ(𝜏 − 𝑛𝑇, 𝜐 − 𝑚𝛥𝑓)𝑒 ( ) . .<label>(8)</label></formula><p>A cascaded combination of OTFS transform with the Wigner transform is performed at the receiver side. It means firstly the received basic pulse is used to filter the signal. Representation of this filtered signal in DD domain is given as</p><formula xml:id="formula_7">𝐴 ᵣ (𝜏, 𝜐) ≜ 𝑒 ( ) 𝑔ᵣ (𝑡 − 𝜏)𝑟(𝑡)𝑑𝑡<label>(9)</label></formula><p>Above signal is sampled at 𝜏 = 𝑛𝑇 and at 𝜐 = 𝑚𝛥𝑓, therefore it becomes</p><formula xml:id="formula_8">𝐴 ᵣ, ( ) (𝜏, 𝜐) = 𝑓(𝜏, 𝜐) * 𝜎𝐴 , (𝜏, 𝜐)<label>(10)</label></formula><p>Therefore, E2E channel may be denoted as</p><formula xml:id="formula_9">(𝜏, 𝜐) = ℎ(𝜏, 𝜐) * 𝜎𝑋[𝑛, 𝑚] * 𝜎𝐴 , (𝜏, 𝜐)<label>(11)</label></formula><p>At the receiver SFFT is performed (on the sample, windowed and then periodized of the signal Z) in order to get the signal. After demodulation, information sequence is received. This sequence is periodic convolution of two-dimensional input signals which are (i) QAM signal and (ii) sampled version of windowed impulse response.</p></div>
<div xmlns="http://www.tei-c.org/ns/1.0"><head>𝑦 [𝑘, 𝑙</head><formula xml:id="formula_10">] = 1 𝑀𝑁 𝑦[𝑛, 𝑚]ℎ 𝑘 − 𝑛 𝑁𝑇 , 𝑙 − 𝑚 𝑀𝛥𝑓 (12) ℎ 𝑘 − 𝑛 𝑁𝑇 , 𝑙 − 𝑚 𝑀𝛥𝑓 = ℎ (𝜐ʹ, 𝜏ʹ)| ʹ , ʹ<label>(13)</label></formula><p>Above equation the channel response is represented by circular convolution having a windowing function.</p><p>From all above equations it is noticed that each of the received symbol obtained has similar channel gain for each transmitted symbol, also for both DD domain it obtains the full diversity <ref type="bibr" target="#b4">[5]</ref>.</p></div>
<div xmlns="http://www.tei-c.org/ns/1.0"><head n="3.">Latest Update in OTFS Field</head><p> OTFS based matched filter algorithm which is used in radar system for determination of velocity and object range. It shows that radar processing depending on OTFS exhibits the basic inherent advantages because of multi carrier modulations but also provides better radar capability i.e., faster tracking rate, longer range and estimation of large Doppler frequency as compared to OFDM based radar <ref type="bibr" target="#b5">[6]</ref>.  OTFS do offers improved PAPR comparing to OFDM and GFDM. This paper considers modulation symbols of an order of M⨯N DD grid (where M are representing number of delay bins and N denotes number of Doppler bins). The simulated CCDF gets represented for the PAPR of OTFS due to varying pulse shape in comparison to OFDM and GFDM <ref type="bibr" target="#b6">[7]</ref>.  To reduce the PAPR, a modified version of ICF was formally suggested in pilot embedded OTFS. This idea is used to denote free degree offered due to guard region. The signal present in guard region varied with a small magnitude by providing afunctional design with proper filtering. The results show that PAPR can be reduced effectively with low BER performance loss.</p><p>[8]  OTFS modulation is beneficial for channels having high Doppler fading and large delay spread channels. It also gives vectorized image of OTFS system in existence of PA and IQI nonlinearity. Twostep process is used to improve the BER performance at the Transmitter. However, at the Receiver impairments must be addressed and compensated to be high resilient to PA and IQI non-linearity in the mm-meter Wave band.[9]  In <ref type="bibr" target="#b9">[10]</ref>, performance of OTFS is tested using common waveforms. It computes the error probability using discrete model of modulation/demodulation. It also discusses the level of diversity that can be attained on fading channels.  In <ref type="bibr" target="#b10">[11]</ref>, OTFS assuming a delay-Doppler channel from two paths and rectangular waveform is studied. It also introduces the concept of Effective Diversity (ED) which is notably effective in comparison to standard diversity in order to transmit higher quantum of symbols. It also examines the condition for which OTFS attains full ED in case of all QAM symbols.  In <ref type="bibr" target="#b11">[12]</ref>, it is shown that OTFS modulation uses a low complexity iterative rake detector. In it OTFS input-output relation is formulated and based on maximum ratio combining strategy. A linear complex iterative rake detector algorithm is proposed for OTFS. Here the BER performance achieved by MRC detector is like MPA detector but with small storage and complexity requirements.  In <ref type="bibr" target="#b12">[13]</ref>, an E2E OFDM based OTFS model is presented in the form of vectorised shape, in which an oscillator having phase noise incorporated at the Transmitter and Receiver. It is also shown that in mm Wave band OTFS is having greater resilient in comparison to phase noise and Doppler shifts.  In <ref type="bibr" target="#b13">[14]</ref>, an efficient message passing MP algorithm was proposed to cancel the ICI and ISI by using appropriate phase shifting. This algorithm is widely used for Doppler spreads. It also shows that error performance of OTFS is better than OFDM under different communication scenarios including low latency communication, ideal and non-ideal form of channel estimation etc.  In <ref type="bibr" target="#b14">[15]</ref>, to minimize the receiver complexity of OTFS modulation a new type of detector is proposed, which is named as Variational Bayes Detector using the optimal MAP detection. It is observed that its complexity is lower than both MP and MAP receiver. It also confirms the superior detection and fast convergence as compared to MP algorithm.  Zhiqiang Wei, who introduced a window design after analysing the effect of transmitter and receiver <ref type="bibr" target="#b15">[16]</ref>. He found that after applying a window at both Tx and Rx an identical performance is achieved. Figure <ref type="figure" target="#fig_2">3</ref> shows that a DC window is applied to increase the channel sparsity by which channel estimation performance is improved.    One of the latest approaches used to design OTFS is Fractionally Spaced Sampling (FSS) approach. FSS receiver have better performance as compared to SSS (traditional) receiver as shown in figure <ref type="figure" target="#fig_5">6</ref>. FSS approach includes following two algorithms: Turbo message passing and Iterative combining message passing <ref type="bibr" target="#b18">[19]</ref>.   A new type of iterative SIC turbo receiver has been investigated, which is having the better performance over existing receivers. Yao Ge in <ref type="bibr" target="#b20">[21]</ref> used a NOMA technique to overcome cochannel interference.</p><p> OTFS operating in delay Doppler domain have performance as compared to OFDM. But due to the presence of residual synchronization error representation of time domain channel is easier as compared to delay Doppler domain representation <ref type="bibr" target="#b21">[22]</ref>. To overcome this inherent nature of DD domain channel a estimation technique based on compressed sensing is introduced <ref type="bibr" target="#b22">[23]</ref>. In which an algorithm based on modified subspace pursuit and orthogonal matching pursuit is introduced. BER performance for these two algorithms is shown in Figure <ref type="figure" target="#fig_7">8</ref>.   </p></div>
<div xmlns="http://www.tei-c.org/ns/1.0"><head n="4.">Advantages and Disadvantages</head><p>In section 3, after taking an overview of latest updates in OTFS field it is noticed that however OTFS has various new opportunities in wireless network of future but still it has several drawbacks. A list of several advantages and disadvantages has been drawn and explained below.</p></div>
<div xmlns="http://www.tei-c.org/ns/1.0"><head n="4.1.">Advantages</head><p> OTFS provide high date rate, better flexibility and reliability as compared to OFDM.  OTFS provides high frequency dispersion. This is because of large Doppler spreads and increased phase noise in millimetre wave communications.  As SNR is increased than BER will get decreased as shown in figure <ref type="figure" target="#fig_10">11</ref> <ref type="bibr" target="#b26">[27]</ref>.    </p></div>
<div xmlns="http://www.tei-c.org/ns/1.0"><head n="5.">Application and Future Scope of OTFS Modulation</head><p>OTFS modulation has large number of application and future scope in next generation wireless networks, as described in the following section Vehicle to Vehicle Communications: Due to increase of vast traffic, Vehicle to Vehicle communications permits various motor vehicles to communicate wirelessly to another motor vehicles or to a Roadside system. It provides various benefits such as management of cooperative traffic, improvements of road -safety and help in autonomous driving. OTFS can play an important role in vehicle-to-vehicle communication over high mobility channel. The current standards used for vehicleto-vehicle communication are IEEE802.11bd and 5G NR V2X.</p><p>Millimetre-wave communications: The millimetre wave for 5g networks provides Giga-bit-persecond communication services by utilizing large amount of under -utilized spectrum at low and medium velocity. By increasing the carrier frequency, Doppler effect becomes more critical. OTFS analyse the impact of Doppler spread, phase noise, and delay spread, which have different value as compared to conventional Radio bands. <ref type="bibr" target="#b4">[5]</ref> <ref type="bibr" target="#b31">[32]</ref> Non-Terrestrial communications: Non-Terrestrial communications contains airborne and space-borne vehicles such as UAVs or High-Altitude Platforms (HAPs) and satellites. It supports 5G networks by providing global coverage and mobility, enhanced network reliability and connectivity. High speed of space-borne and airborne vehicles provides large Doppler spread, which can be easily handled by OTFS modulation. In order to overcome the limited computing capability and on-board power supply of space-borne and airborne platform, OTFS offers an important feature having low complexity and low PAPR.</p><p>Underwater Acoustic (UWA) communications: Due to limited bandwidth, high delay spread and rapid time variations, Under Acoustic (UA) channels are one of the most challenging wireless channels. For UWA communication some of the most popular single carrier modulation schemes are OFDM, Orthogonal Signal Division Multiplexing (OSDM) and Decision Feedback Equalizers (DFE).However all of them transmit information in time frequency domain in which ICI and ISI equalization is one of the tedious task. UWA channels operate in DD domain which has easier equalization than that of TF domain <ref type="bibr" target="#b32">[33]</ref>.</p></div>
<div xmlns="http://www.tei-c.org/ns/1.0"><head n="6.">Conclusion</head><p>This paper gives a detailed description of OTFS as one of the emerging two-dimensional modulation for future wireless network with an overview of basic concept of OTFS modulation and demodulation in DD domain with its basic diagram. Most popular advantage of OTFS having high frequency dispersion, lower BER, lower PAPR with its critical challenge of receiver complexity are highlighted with waveform description. The potential applications have been discussed with example and latest research in the field thereby highlighting the latest updates in OTFS modulation in a genuine manner. This review paper will meet the expectation of readers and will lead future research in this area for designing next generation networks.</p></div><figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_0"><head>Figure 1 :</head><label>1</label><figDesc>Figure 1: Wireless network with multipath fading between Tx and RxLet the signal transmitted is s(t) than signal received is r(t) be given by</figDesc><graphic coords="2,188.52,264.72,235.92,144.00" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_1"><head>Figure 2 :</head><label>2</label><figDesc>Figure 2: Block diagram of OTFS modulation: Transmitter and Receiver</figDesc><graphic coords="3,114.00,67.80,383.52,177.24" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_2"><head>Figure 3 :</head><label>3</label><figDesc>Figure 3: Comparison of performance of Channel estimation after applying DC window  One of the major issues in OTFS is selection of receiver antenna for better performance. SIMO-OTFS and MIMO-OTFS are the basic parameter for selection of receiver antenna. The comparison shows that MIMO-OTFS have better performance as compare to SIMO-OTFS as given in figure 4(a) and figure 4(b)[17].</figDesc><graphic coords="6,197.04,287.16,217.56,146.64" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_3"><head>Figure 4 (</head><label>4</label><figDesc>Figure 4 (a): BER performance of SIMO-OTFS</figDesc><graphic coords="6,204.12,446.52,203.40,146.52" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_4"><head>Figure 5 :</head><label>5</label><figDesc>Figure 5: Complexity comparison of various linear detectors for OTFS and OFDM</figDesc><graphic coords="7,221.64,67.80,202.20,146.52" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_5"><head>Figure 6 :</head><label>6</label><figDesc>Figure 6: BER performance comparison of OTFS with dissimilar traditional Rx design  To enhance the performance of OTFS modulation a cross domain iterative detection algorithm is introduced. It is different from conventional OTFS detection method. This algorithm is applied to both time domain and DD domain. BER performance for OTFS modulation with fractional Doppler shifts for P=10 is shown in figure 7[20].</figDesc><graphic coords="7,209.16,502.80,192.96,139.20" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_6"><head>Figure 7 :</head><label>7</label><figDesc>Figure 7: BER performance for OTFS with fractional Doppler shift.</figDesc></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_7"><head>Figure 8 :</head><label>8</label><figDesc>Figure 8: BER and SNR performance for MSP and OSP algorithm  In high-speed vehicle communication OTFS has drawback of power emission outside the frequency band. To overcome this, a novel PHY layer is developed by introducing Windowing and Restructuring (WR) OTFS system.In figure9(a), 9(b), 9(c) it is shown that WR-OTFS have better power rejection outside frequency band as compared to OFDM and OTFS scheme.<ref type="bibr" target="#b23">[24]</ref> </figDesc><graphic coords="8,184.20,364.68,243.12,133.20" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_8"><head>Figure 9 (Figure 9</head><label>99</label><figDesc>Figure 9(c): Power rejection outside frequency band in WR-OTFS scheme BER performance for different user equipment speed at AWGN and DD channel is shown in figure 9(d)</figDesc><graphic coords="9,187.32,288.96,236.40,154.32" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_9"><head>Figure 10 :</head><label>10</label><figDesc>Figure 10: Performance improvement of OTFS by optimizing pilot and data overhead</figDesc><graphic coords="9,187.92,542.04,235.80,167.04" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_10"><head>Figure 11 :</head><label>11</label><figDesc>Figure 11: Relationship between BER and SNR</figDesc><graphic coords="10,201.24,224.76,209.04,162.72" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_11"><head>Figure 12 :</head><label>12</label><figDesc>Figure 12: BER comparison of MIMO-OFDM and MIMO-OTFS  It also allows longer ranges for Radar applications and faster target tracking rate.  OTFS provides a lower PAPR for better communication coverage as compared to OFDM and GFDM as shown in below figure13[29].</figDesc><graphic coords="10,188.04,435.12,236.52,139.80" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_12"><head>Figure 13 :</head><label>13</label><figDesc>Figure 13: Comparison of PAPR for OTFS, OFDM and GFDM OTFS have better performance as compared to OFDM over high mobility channel. As shown in figure 14<ref type="bibr" target="#b29">[30]</ref> </figDesc><graphic coords="11,209.52,257.28,192.48,144.00" type="bitmap" /></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" xml:id="fig_13"><head>Figure 14 :</head><label>14</label><figDesc>Figure 14: Comparison of performance of OTFS and OFDM over high mobility channel</figDesc></figure>
<figure xmlns="http://www.tei-c.org/ns/1.0" type="table" xml:id="tab_0"><head></head><label></label><figDesc>) 𝑙=0, 1…. 𝘔-1and 𝑘=0, 1…. 𝘕-1.</figDesc><table><row><cell cols="4">While in the receiver side, SFFT of 𝑌 [𝘯, 𝘮] is used in inverse process, to obtain 𝑦 [𝑘, 𝑙] = SFFT</cell></row><row><cell>(𝑌[𝑛,𝑚]) for</cell><cell></cell><cell></cell><cell></cell></row><row><cell>𝑦[𝑘, 𝑙] =</cell><cell>𝑌[𝑛, 𝑚] 𝑒</cell><cell>(</cell><cell>)</cell></row></table></figure>
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		<title level="a" type="main">Orthogonal Time Frequency Space Modulation</title>
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