Digital Filter Arrangement for Compensating Group Velocity Dispersion in an Optical Transmission System
20230129067 · 2023-04-27
Inventors
Cpc classification
H04B10/25253
ELECTRICITY
H04B10/614
ELECTRICITY
International classification
Abstract
The present disclosure relates to a digital filter arrangement (DFA) for compensating group velocity dispersion (GVD) in an optical transmission system (OTS) wherein the DFA is configured to receive a sequence of samples of a digital input signal in the time domain in the form of consecutive blocks of size L. The DFA is configured to generate M discrete Fourier transforms of a current overlap block of a size N greater than the size L and of M−1 delayed versions of the current overlap block. The DFA is configured to filter the entries of the generated M discrete Fourier transforms to generate an output discrete Fourier transform with N entries, wherein the compensation filter is implemented by a delay network and a linear combination algorithm.
Claims
1. A digital filter arrangement (DFA), comprising: a receiver; M discrete Fourier transform (DFT) filters, wherein each DFT filter of the M DFT filters is implemented by a fast Fourier transform (FFT) algorithm of a size Γ smaller than a size N and by an interpolation algorithm; and a compensation filter, implemented by a delay network and a linear combination algorithm; wherein the receiver is configured to: receive a sequence of samples of a digital input signal in the time domain in the form of consecutive blocks of size L, wherein each block of the blocks comprises L consecutive samples of the digital input signal; wherein the M DFT filters are configured to: generate M discrete Fourier transforms of a current overlap block and of M−1 delayed versions of the current overlap block, wherein the current overlap block is of the size N and the size N is greater than the size L, wherein each generated discrete Fourier transform is of the size N and comprises N entries, the current overlap block comprises samples of a current block of the blocks and the N-L last consecutive samples of a directly previous block that was received by the DFA directly before the current block of the blocks, and wherein the compensation filter is configured to: filter the N entries of the generated M discrete Fourier transforms to generate an output discrete Fourier transform with N entries.
2. The DFA according to claim 1, further comprising: an inverse discrete Fourier transformation (IDFT) filter, configured to generate, on the basis of the output discrete Fourier transform, an output block of size N.
3. The DFA according to claim 2, wherein the DFA is configured to: generate an output block of the size L on the basis of the output block of the size N, by using an overlap-add or an overlap-save method.
4. The DFA according to claim 1, wherein the size L of each block is the product of M and Δ, L=M.Math.Δ, wherein M and Δ are each a positive integer.
5. The DFA according to claim 1, wherein: the size N of the current overlap block is the product of Δ with the sum of M and m, N=Δ.Math.(M+m), wherein m is a positive integer, and the product of Δ and m, A m, corresponds to the number of last consecutive samples in the sequence of samples of the directly previous block.
6. The DFA according to claim 1, wherein the DFA is configured to generate, on the basis of the current block, the current overlap block of the size N and greater than the size L; and generate the M−1 delayed versions of the current overlap block; and wherein the M DFT filters are configured to: jointly approximate, on the basis of the current overlap block and the M−1 delayed versions of the current overlap block, the M discrete Fourier transforms.
7. The DFA according to claim 6, wherein the DFA is configured to generate the M−1 delayed versions of the current overlap block by progressively delaying the current overlap block in steps of Δ samples.
8. The DFA according to claim 1, wherein the DFA is configured to split the current block into M subblocks each of a size Δ, wherein each subblock comprises Δ consecutive samples of the current block; and zero-pad each subblock to a zero-padded sequence of the size Γ comprising F samples, wherein each zero-padded sequence comprises the Δ samples of the corresponding subblock and Γ-A zeros; and wherein the M DFT filters are configured to: jointly approximate, on the basis of the M zero-padded sequences, M further discrete Fourier transforms; and generate the M discrete Fourier transforms by: delaying the M further discrete Fourier transforms, and aligning and adding one or more of the M delayed further discrete Fourier transforms and one or more of the M further discrete Fourier transforms.
9. The DFA according to claim 8, wherein the M DFT filters are configured to perform the alignment by performing a symbol-wise multiplication of one or more delayed further discrete Fourier transforms or one or more further discrete Fourier transforms by a rotation vector.
10. The DFA according to claim 8, wherein the DFA is configured to: group the Δ samples of each subblock into two parts of samples; carry out the zero-padding of each subblock to a zero-padded sequence of the size Γ by adding Γ-Δ zeros between the two parts of samples; and wherein the M DFT filters are configured to jointly approximate, on the basis of the M zero-padded sequences, the M further discrete Fourier transforms.
11. The DFA according to claim 10, wherein each of the M DFT filters are configured to jointly approximate, on the basis of the M zero-padded sequences, the M further discrete Fourier transforms by: transforming each zero-padded sequence by the FFT algorithm of the size Γ to a discrete Fourier transform of the size F; interpolating the Γ samples of each discrete Fourier transform of the size Γ to N samples of another discrete Fourier transform of the size N by a low-pass filter; and performing a symbol-wise multiplication of the samples of each other discrete Fourier transform by a rotation vector to obtain the respective further discrete Fourier transform.
12. The DFA according to claim 1, wherein the compensation filter comprises N subfilters, wherein each subfilter is implemented by the delay network and the linear combination algorithm; and wherein the DFA is configured to perform a filtering on a k.sup.th entry of one or more of the generated M discrete Fourier transforms by using a k.sup.th subfilter to generate a k.sup.th entry of the output Fourier transform, wherein each discrete Fourier transform comprises N entries.
13. The DFA according to claim 1, wherein the compensation filter comprises N subfilters, and a k.sup.th subfilter of the N subfilters is configured to generate a k.sup.th entry of the output Fourier transform as a linear combination of: a k.sup.th entry of one or more first discrete Fourier transforms of the M discrete Fourier transforms; or a k.sup.th entry of one or more delayed versions of one or more second discrete Fourier transforms of the M discrete Fourier transforms.
14. The DFA according to claim 13, wherein the k.sup.th subfilter is configured to perform the linear combination by weighting the k.sup.th entry of the one or more first discrete Fourier transforms, or the k.sup.th entry of the one or more delayed versions of the one or more second discrete Fourier transforms with a respective coefficient.
15. The DFA according to claim 13, wherein the k.sup.th subfilter is configured to generate the k.sup.th entry of each of the one or more delayed versions of each of the one or more second discrete Fourier transforms by delaying the k.sup.th entry of the respective second discrete Fourier transform using one or more integer delays.
16. An optical transmission system (OTS), comprising: one or more optical fibers; a transmitter; and a receiver; wherein the transmitter is configured to transmit, on the basis of a first digital signal, a modulated light signal via the one or more optical fibers to the receiver; wherein the receiver is configured to receive the modulated light signal via the one or more optical fibers from the transmitter and convert the received modulated light signal into a second digital signal; wherein: the transmitter is configured to pre-compensate group velocity dispersion (GVD) of the modulated light signal on the basis of the first digital signal using a digital filter arrangement (DFA), or the receiver is configured to compensate GVD of the received modulated light signal on the basis of the second digital signal using a DFA; and wherein the DFA comprises: a DFA receiver; M discrete Fourier transform (DFT) filters, wherein each DFT filter of the M DFT filters is implemented by a fast Fourier transform (FFT) algorithm of a size Γ smaller than a size N and by an interpolation algorithm; and a compensation filter, implemented by a delay network and a linear combination algorithm; wherein the DFA receiver is configured to: receive a sequence of samples of a digital input signal in the time domain in the form of consecutive blocks of size L, wherein each block of the blocks comprises L consecutive samples of the digital input signal; wherein the M DFT filters are configured to: generate M discrete Fourier transforms of a current overlap block and of M−1 delayed versions of the current overlap block, wherein the current overlap block is of the size N and the size N is greater than the size L, wherein each generated discrete Fourier transform is of the size N and comprises N entries, the current overlap block comprises samples of a current block of the blocks and the N-L last consecutive samples of a directly previous block that was received by the DFA directly before the current block of the blocks, and wherein the compensation filter is configured to: filter the N entries of the generated M discrete Fourier transforms to generate an output discrete Fourier transform with N entries.
17. The OTS according to claim 16, wherein the DFA further comprises an inverse discrete Fourier transformation (IDFT) filter configured to generate, on the basis of the output discrete Fourier transform, an output block of size N.
18. The OTS according to claim 17, wherein the DFA is configured to generate an output block of the size L on the basis of the output block of the size N, by using an overlap-add or an overlap-save method.
19. A method, comprising: receiving a sequence of samples of a digital input signal in the time domain in the form of consecutive blocks of size L, wherein each block comprises L consecutive samples of the digital input signal; generating M discrete Fourier transforms of a current overlap block and of M−1 delayed versions of the current overlap block by using M discrete Fourier transform (DFT) filters, wherein the current overlap block is of a size N greater than the size L, each generated discrete Fourier transform is of the size N and comprises N entries, the current overlap block comprises the samples of a current block and the N-L last consecutive samples of a directly previous block that was received directly before the current block, and each DFT filter of the M DFT filters is implemented by a fast Fourier transform (FFT) algorithm, of a size Γ smaller than the size N and by an interpolation algorithm; and filtering, by a compensation filter, the entries of the generated M discrete Fourier transforms to generate an output discrete Fourier transform with N entries, wherein the compensation filter is implemented by a delay network and a linear combination algorithm.
20. A non-transitory computer readable medium storing executable program code which, when executed by a processor, causes the method according to claim 19 to be performed.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0109] The above described aspects and implementation forms will be explained in the following description of specific embodiments in relation to the enclosed drawings, in which:
[0110]
[0111]
[0112]
[0113]
[0114]
[0115]
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DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS
[0119]
[0120] The above description of the DFA according to the first aspect and its implementation forms is correspondingly valid for the DFA of
[0121] The DFA 1 of
[0122] The first part 2 of the DFA 1 comprises M discrete Fourier transform (DFT) filters 2a. The first part 2 of the DFA may be configured to receive the sequence of samples of the digital input signal in the time domain in the form of consecutive blocks S respectively S(μ) of size L, wherein each block comprises L consecutive samples of the digital input signal. The “μ” corresponds to a time point, such as the time point of the clock of a processor for executing the function of the DFA 1.
[0123] The first part 2 of the DFA 1 may be configured to generate M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M of a current overlap block of a size N greater than the size L and of M−1 delayed versions of the current overlap block by using the M DFT filters 2a. In other words, the first part 2 of the DFA may be configured to perform for a current block a transformation from the time domain to the frequency domain using the M DFT filters 2a generating M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M for a current overlap block of a size N greater than the size L and M−1 delayed versions of the current overlap block, wherein the current overlap block is based on the current block. The M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M are the results of the transformation from the time domain to the frequency domain.
[0124] Each DFT filter of the M DFT filters 2a is implemented by a DFT algorithm of a size F smaller than the size N and by an interpolation algorithm. The DFT algorithm of the size Γ may be a fast Fourier transform (FFT) algorithm of the size N.
[0125] The size L of each block S respectively S(μ) is the product of M and Δ (L=M.Math.Δ), wherein M and Δ are each a positive integer. The size N of the current overlap block is the product of Δ with the sum of M and m (N=Δ.Math.(M+m)), wherein m is a positive integer and the product of Δ and m (Δ.Math.m) corresponds to the number of last consecutive samples in the sequence of samples of the directly previous block.
[0126] Each generated discrete Fourier transform of the M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M is of the size N and comprises N entries. The entries may also be referred to as Fourier coefficients or Fourier components. The current overlap block comprises the samples of the current block and the N-L last consecutive samples of a directly previous block that was received by the first part 2 of the DFA 1 directly before the current block.
[0127] The second part 3 of the DFA 1 corresponds to a compensation filter. The compensation filter 3 is configured to filter the entries of the generated M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M to generate an output discrete Fourier transform Y with N entries Y.sub.1, Y.sub.2, . . . , Y.sub.N. The output discrete Fourier transform Y is compensated with respect to the GVD. The compensation filter 3 is implemented by a delay network 3a and a linear combination algorithm 3b.
[0128] As a result of the frequency domain filtering using the compensation filter 3 the complexity of the DFA 1 is reduced, because a frequency domain implementation of filtering comprises a lower complexity compared to time domain implementations. Namely, in contrast to a time domain implementation of filtering, in a frequency domain implementation of filtering the number of operations per sample grows logarithmically instead of linearly with the filter size. In addition, as a result of using the DFT filters 2a the complexity of the DFA is further reduced. That is, the transformation of the samples from the time domain to the frequency domain using the DFT filters 2a requires a lower complexity compared to performing a normal DFT algorithm. Namely, for transforming a sequence of N samples from the time domain to the frequency domain a DFT algorithm of size N and, thus, a DFT filter of size N is normally required. In contrast thereto, the present disclosure proposes to use the M DFT filters 2a, wherein each DFT filter 2a is implemented by a DFT algorithm of a size Γ smaller than the size N and by an interpolation algorithm. That is, the present disclosure proposes to reduce the size of the DFT algorithm from N to F and to compensate this reduction by additionally performing an interpolation algorithm.
[0129] As outlined already above, the DFA 1 may be used in a receiver and/or a transmitter of an optical transmission system. Thus, the sequence of input blocks S may correspond to the complex baseband signal that shall be pre-compensated at the transmitter or post-compensated at the receiver in case of using one or more single-mode fibers for communication in an optical transmission system, in which the transmitter respectively receiver is provided. Since, as discussed above, GVD compensation may be applied separately to orthogonal polarizations, only one polarization is considered. The filtering using the DFA 1 for GVD compensation may also be applied to the second polarization, if necessary.
[0130] The DFA 1 may be implemented by hardware and/or software.
[0131] The DFA 1 according to
(M and m are each a positive integer). This is advantageous, because arbitrarily chosen low overlap ratios are possible by increasing the number M of DFT filters 2a. Due to the efficient joint approximation (joint computation) of the M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M using the M DFT filters 2a, this results in complexity savings. The size N of the used M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M may be reduced by increasing their number M. Due to the efficient joint computation of the M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M using the M DFT filters 2a, this results in complexity savings at equal or better group velocity dispersion (GVD) tolerance.
[0132] According to an implementation form, the M DFT filters 2a and, thus, the M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M may be progressively activated on demand according to the requested GVD tolerance in order to save complexity and power consumption over shorter links.
[0133]
[0134] The above description of the DFA according to the first aspect and its implementation forms is correspondingly valid for the DFA of
[0135] The DFA 1 of
[0136] As shown in
[0137] Therefore, as shown in
[0138] According to the embodiment of
[0139] As shown in
[0140] Further, as shown in
[0141] The description with respect to a k.sup.th subfilter 3.sub.k of the compensation filter 3 is valid for each subfilter of the N subfilters 3.sub.1, 3.sub.2, . . . , 3.sub.N of the compensation filter 3.
[0142] According to
[0143] As shown in
[0144] The one or more delayed versions of a discrete Fourier transform may differ to each other by a delay of multiples of L samples in the time domain or a delay of multiples of blocks of the respective discrete Fourier transform in the frequency domain. That is, a delayed version of a discrete Fourier transform may correspond to the discrete Fourier transform delayed by a delay of multiples of blocks of the discrete Fourier transform in the frequency domain.
[0145] The k.sup.th subfilter 3.sub.k is configured to generate, using the respective linear combination algorithm 3b, the k.sup.th entry of the output Fourier transform as a linear combination of the k.sup.th entry of one or more discrete Fourier transforms (may be referred to as “one or more first discrete Fourier transforms”) of the M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M and/or the k.sup.th entry of one or more delayed versions of one or more discrete Fourier transforms (may be referred to as “one or more second discrete Fourier transforms”) of the M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M. The k.sup.th entry of the one or more delayed versions of the one or more second discrete Fourier transforms is generated by the respective delay network 3a of the k.sup.th subfilter 3k, as shown in
[0146] Some or all of the one or more first discrete Fourier transforms and of the one or more second discrete Fourier transforms may correspond to each other.
[0147] The k.sup.th subfilter may be configured to perform the linear combination by weighting the k.sup.th entry of the one or more first discrete Fourier transforms, and/or the k.sup.th entry of the one or more delayed versions of the one or more second discrete Fourier transforms with a respective coefficient.
[0148] The k.sup.th subfilter may be configured to linearly combine the k.sup.th entry of the one or more first discrete Fourier transforms and/or the k.sup.th entry of the one or more delayed versions of the one or more discrete Fourier transforms by using one or more corresponding coefficients of the linear combination algorithm.
[0149] As shown in
[0150] As described above, according to the embodiment of
[0151] In a first step, each current block S of the size L (L=M.Math.Δ) comprising L input samples may be extended to a corresponding current overlap block s.sub.1 of size N (N=(M+m).Math.Δ) comprising N samples by using an overlap technique. The overlap technique may correspond to an overlap-add or an overlap-save technique. The terms “overlap block” and “extended input block” may be used as synonyms.
[0152] In a second step, M−1 delayed versions s.sub.2, . . . , s.sub.M of the respective current overlap block s.sub.1 may be generated. Each copy s.sub.2, . . . , s.sub.M of the respective current overlap block s.sub.1 is successively delayed by Δ samples.
[0153] In a third step, M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M may be jointly computed, using the M DFT filters 2a, on the basis of the respective current overlap block s.sub.1 and the M−1 delayed versions of the respective current overlap block s.sub.2, . . . , s.sub.M.
[0154] In a fourth step, the k.sup.th entry Y.sub.k of the output discrete Fourier transform Y (k=1, . . . , N) may be computed, using the compensation filter 3, as a linear combination of the k.sup.th entry of one or more suitable first discrete Fourier transforms of the M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M and/or the k.sup.th entry of one or more suitably delayed versions of one or more suitable second discrete Fourier transforms of the M discrete Fourier transforms X.sub.1, X.sub.2, . . . , X.sub.M. The sets of first and second discrete Fourier transforms may optionally have non-empty intersection. That is, optionally, some or all of the one or more first discrete Fourier transforms and of the one or more second discrete Fourier transforms may correspond to each other.
[0155] In an optional fifth step, the output block y of size N may be computed, by using the IDFT filter 4, on the basis of the output discrete Fourier transform Y.
[0156] In an optional sixth step, m.Math.Δ overlapping samples may be removed from the output block y to obtain the block R of the size L (L=M.Math.Δ) comprising L output samples. The optional overlap removal unit 4a shown in
[0157] According to the embodiment of
[0158] Y.sub.k [μ]=Σ.sub.i=0.sup.l−1c.sub.k,i.Math.DFT.sub.k (D.sup.(i+P.sup.
Y.sub.k[μ]=Σ.sub.i=0.sup.l−1c.sub.k,i.Math.DFT.sub.k(D.sup.(i+P.sup.
[0159] The k.sup.th entry may also be referred to as the k.sup.th discrete Fourier transform (DFT) component (in short: k.sup.th Fourier component) or as the k.sup.th Fourier coefficient.
[0160] In the above equation (1), D.sup.n represents a delay of n samples, DFT.sub.k is a k.sup.th Fourier coefficient (k.sup.th entry) of a discrete Fourier transform, Ŝ[μ] denotes the μ.sup.th overlap block (μ.sup.th block (input block) of the size L (L=M.Math.Δ) extended by an overlap section of the size m.Math.Δ), l is the number of coefficients in the linear combination, c.sub.k,i is a coefficient of the linear combination (which may be optimized as described below), and p.sub.k is an integer number (which may be optimized as described below) corresponding to an integer delay of p.sub.k Δ samples. In particular, c.sub.k,i may be a coefficient of one or more coefficients of the linear combination algorithm 2c of the k.sup.th subfilter 3.sub.k of the compensation filter 3 (as shown below in equation (3)). Further, p.sub.k may be an integer number corresponding to an integer delay of one or more integer delays of the delay network 2b of the k.sup.th subfilter 3k (as shown below in equations (2) and (3)).
[0161] The term “D.sup.(i+p.sup.
[0162] (i+p.sub.k).Math.Δ=q.sub.k,i.Math.L+r.sub.k,i∈{0, 1, . . . , M−1}p.sub.kM The equality
(i+p.sub.k).Math.Δ=q.sub.k,i.Math.L+r.sub.k,i.Math.Δq.sub.k,ir.sub.k,i∈{0,1, . . . ,M−1}i+p.sub.kM (2)
[0163] (i+p.sub.k) Δ=q.sub.k,i.Math.L+r.sub.k,i.Math.Δq.sub.k,ir.sub.k,i ∈{0, 1, . . . , M−1}i+p.sub.kMholds, wherein the integers and denote the quotient and the remainder of the integer division of by.
[0164] Y.sub.k[μ]=Σ.sub.i=1.sup.l−1c.sub.k,i.Math.D.sup.q.sup.
Y.sub.k[μ]=Σ.sub.i=1.sup.l−1c.sub.k,i.Math.D.sup.q.sup.
[0165] Y.sub.k[μ]=Σ.sub.i=1.sup.l−1c.sub.k,i.Math.D.sup.q.sup.
[0166] The above equation (3) shows that the linear combination according to the above equation (1) is compatible with the block diagram of
[0167] In the following an optional optimization process of the coefficients c.sub.k,i and integer delays p.sub.k for k=1, . . . , N and i=0, 1, . . . , l−1 is described, in case the DFA 1 uses an overlap technique, such as an overlap-discard or overlap-add method, for generating a current overlap block of a current block received by the DFA 1.
[0168] For such an optimization the constraint is posed that the phase response of the compensation filter 3 of the DFA 1 (which may also be referred to as equalizer filter) is the inverse of the GVD phase response, except for an immaterial frequency-independent phase rotation and delay. The optimization target is the minimization of the time-domain aliasing resulting from the overlap technique (e.g. overlap-discard or overlap-add method). In other terms, the target is to acquire an exact inversion of the GVD response in the frequency domain. Since the equivalent impulse response may exceed the overlap length (Δ.Math.m), it is a target that a proper measure (described below) of the resulting time-domain aliasing is minimized.
[0169] Σ.sub.i=0.sup.l−1c.sub.k,i.Math.exp(−j.Math.2π.Math.(i+p.sub.k).Math.Δ.Math.f.sub.k)=h.sub.k (k=1, . . . , N)h.sub.k−0.5≤f.sub.k≤0.5 In mathematical terms the constraint may read
Σ.sub.i=0.sup.l−1c.sub.k,i.Math.exp(−j.Math.2π.Math.(i+p.sub.k).Math.Δ.Math.f.sub.k)=h.sub.k(k=1, . . . ,N)h.sub.k−0.5≤f.sub.k≤0.5,(4)
[0170] Σ.sub.i=0.sup.l−1c.sub.k,i.Math.exp(−j.Math.2π.Math.(i+p.sub.k).Math.Δ.Math.f.sub.k)=h.sub.k (k=1, . . . , N)h.sub.k−0.5≤f.sub.k≤0.5 wherein is the k.sup.th Fourier coefficient (entry) of a discrete Fourier transform of the inverse GVD phase response and is the normalized frequency associated with the k.sup.th Fourier coefficient.
[0171] (a+1)X.sub.aY.sub.k [μ]Z.sub.a,k [μ]Z.sub.a,k [μ]Σ.sub.i=0.sup.l−1c.sub.k,i.Math.DFT.sub.k ((D.sup.r.sup.
(a+1)X.sub.aY.sub.k[μ]Z.sub.a,k[μ]Z.sub.a,k[μ]Σ.sub.i=0.sup.l−1c.sub.k,i.Math.DFT.sub.k((D.sup.r.sup.
[0172] (a+1)X.sub.aY.sub.k [μ]Z.sub.a,k [μ]Z.sub.a,k [μ]Σ.sub.i=0.sup.l−1c.sub.k,i.Math.DFT.sub.k ((D.sup.r.sup.
[0173] DFT.sub.k(a+1)DFT.sub.k (D.sup.(i+p.sup.
DFT.sub.k(a+1)DFT.sub.k(D.sup.(i+p.sup.
[0174] DFT.sub.k(a+1)DFT.sub.k (D.sup.(i+p.sup.
[0175] Several choices of the norm are possible. If the infinite norm or the L.sub.1 distance (L.sub.1 norm) are used, a mixed-integer linear programming problem is obtained. In case of the Euclidean norm, a least-square problem is obtained. Both types of problems may be solved by using standard numerical routines.
[0176] The solution of the optional optimization problem may be done by a usual optimization routine. The approach to define the optional optimization problem consists of two steps:
[0177] In a first step the response of the DFA 1 between the points after the overlap unit 2b and before the overlap removal unit 4a is constrained to be the inverse of the GVD function. In a second step the time-domain aliasing is minimized. The time-domain aliasing is defined using a proper norm of M equivalent impulse responses z.sub.a for a=0, 1, . . . , M−1. The (a+1)-th equivalent impulse response is obtained when all the Fourier coefficients of the (a+1)-th Fourier transform X.sub.a of the M discrete Fourier transforms X.sub.1, . . . , X.sub.M are equal to 1 and all the Fourier coefficients of the remaining M−1 Fourier transforms X.sub.i (i ∈{1, 2, . . . , M}, i≠a+1) of the M discrete Fourier transforms X.sub.1, . . . , X.sub.M are equal to 0.
[0178] A DFA that is equivalent to the DFA of
[0179]
[0180] According to
[0181] Further, as shown in
[0182]
[0183] According to
The base rotation vector may be as follows:
wherein j is the imaginary unit.
For example, as can be seen from
[0184]
[0185] The above description of the DFA according to the first aspect and its implementation forms is correspondingly valid for the DFA of
[0186] According to an embodiment of the present disclosure, the generation of the M further discrete Fourier transforms (which may also be referred to as “input-pruned discrete Fourier transforms”) shown in
[0187] The DFA is configured to group the Δ samples of each subblock of the M subblocks into two parts of samples x− and x+. Optionally, the DFA may be configured to group the A samples of each subblock of the M subblocks into two equal parts of samples x− and x+. The M subblocks form a current block S of the size L (L=M.Math.Δ) received by the DFA (not shown in
[0188] In a second step S51 following the first step, the DFA is configured to carry out a zero-padding of each subblock to a zero-padded sequence of the size Γ (Γ>Δ) by adding Γ-A zeros between the two parts of samples x− and x+ (Γ is smaller than N). Γ may beneficially be a positive integer. As a result in the second step S51 starting with a subblock corresponding to the sequence of samples [x−, x+] the zero-padded sequence [x+, 0, . . . , 0, x−] is generated, wherein the zero-padded sequence [x+, 0, . . . , 0, x−] comprises the two parts of samples x− and x+ of the subblock and Γ-Δ zeros. The zero-padding introduces excess bandwidth and allows for interpolation, which is performed in the step S53. According to an embodiment, Γ may be assumed to be
[0189] As shown in
[0190] The first and second part x+ and x− may be arranged in the respective subblock, such that in the sequence of consecutive samples of the respective subblock the samples of the second part x− are arranged previous to the samples of the first part x+. That is, the subblock may correspond to the sequence [x−, x+]. That is, the samples of the second part x− may be arranged at the beginning and the samples of the first part x+ may be arranged at the end of the respective subblock.
[0191] As shown in
[0192] In a third step S52 following the second step S51, the zero-padded sequence generated in the second step S51 is transformed by a DFT algorithm of the size Γ to a discrete Fourier transform DFT.sub.Γ([x+, 0, . . . , 0, x−]) of the size F. The DFT algorithm of the size Γ may be a fast Fourier transform (FFT) algorithm.
[0193] In a fourth step S53 following the second step S52, the DFA is configured to interpolate, using an interpolation algorithm, the Γ samples of the discrete Fourier transform DFT.sub.Γ([x+, 0, . . . , 0, x−]) of the size F, generated in the step S52, to N samples of another discrete Fourier transform DFT.sub.N([x+, 0, . . . , 0, x−]) of the size N (N=(M+m).Math.Δ). The discrete Fourier transform DFT.sub.Γ([x+, 0, . . . , 0, x−]) of the size Γ may be interpolated from Γ samples to N samples using a low-pass real filter.
[0194] In a fifth step S54 following the fourth step S53, the DFA is configured to perform a symbol-wise multiplication of the samples of the other discrete Fourier transform DFT.sub.N([x+, 0, . . . , 0, x−]) by a rotation vector ρ_2.sub.M+m to obtain the respective further Fourier transform DFT.sub.N([0, . . . , 0, x−, x+,]) of the size N.
[0195] The symbol-wise multiplication of the samples of each other discrete Fourier transform by the rotation vector in step S54 corresponds to a shift in the time domain of the non-zero samples of the respective zero-padded sequence. Therefore, as shown in
The rotation vector may be as follows:
wherein j is the imaginary unit.
[0196] The interpolation may be implemented by using a polyphase finite impulse response (FIR) filter, wherein the input of the polyphase FIR filter is regarded as periodic.
[0197] The DFT algorithm of the above described third step S52 and the interpolation algorithm of the above described fourth step S53 implement a DFT filter of the M DFT filters used by the DFA for generating the M further discrete Fourier transforms. As shown with respect to
[0198]
[0199] The above description of the DFA according to the first aspect and its implementation forms is correspondingly valid for the DFA of
[0200] The DFA of
[0201] As shown in
[0202] In a first step S61 the DFA is configured to split a current block S respectively S(μ) into M subblocks each of the size Δ, wherein each subblock comprises Δ samples of the current block S. A subblock of the size Δ corresponds to a sequence of samples of the length A. For example, as shown in
[0203] As shown in
[0204] In a second step S62 following the first step S61, the DFA is configured to zero-pad each subblock to a zero-padded sequence of the size Γ comprising Γ samples (Γ<N), wherein each zero-padded sequence comprises Δ samples of the corresponding subblock and Γ-Δ zeros. Further, in the second step S62 the DFA is configured to jointly approximate on the basis of the M zero-padded sequences, M further discrete Fourier transforms (input-pruned Fourier transforms) of the size N (N=Δ. (M+m)) by using the M DFT filters (each DFT filter is implemented by a DFT algorithm of the size Γ and an interpolation algorithm). For example m may equal to one (m=1). In this case, as shown in
[0205] The DFA is configured to generate the M (e.g. M=3) discrete Fourier transforms X.sub.1, X.sub.2, X.sub.3 on the basis of the M further discrete Fourier transforms DFT([0, 0, 0, z.sub.k]), DFT([0, 0, 0, z.sub.k-1]) and DFT([0, 0, 0, z.sub.k-2]), generated in the second step S62, by performing a third step S63 following the second step S62 and a fourth step S64 following the third step S63. In the third step S63, the DFA is configured to delay the M further discrete Fourier transforms to generate M delayed further discrete Fourier transforms DFT([0, 0, 0, z.sub.k-3]), DFT([0, 0, 0, z.sub.k-4]), DFT([0, 0, 0, z.sub.k5]). In the third step the M further discrete Fourier transforms are delayed in order to provide with the delayed versions enough samples of a directly previous block received by the DFA directly before the current block S or of more than one previous block received by the DFA before the current block S for generating the M discrete Fourier transforms X.sub.1, X.sub.2 and X.sub.3.
[0206] In the fourth step S64, the DFA is configured to align and add one or more of the M delayed further discrete Fourier transforms DFT([0, 0, 0, z.sub.k3]), DFT([0, 0, 0, z.sub.k4]), DFT([0, 0, 0, z.sub.k-5]) and one or more of the M further discrete Fourier transforms DFT([0, 0, 0, z.sub.k]), DFT([0, 0, 0, z.sub.k-1], DFT([0, 0, 0, z.sub.k-2]) to generate the M discrete Fourier transforms X.sub.1, X.sub.2, X.sub.3. The time shift necessary to align the one or more further discrete Fourier transforms and one or more delayed further discrete Fourier transforms is implemented in the frequency domain via a symbol-wise multiplication of the respective further discrete Fourier transforms and respective delayed further discrete Fourier transforms by suitable powers of the rotation vector ρ_1.sub.M+m, (which corresponds to p_1.sub.4 in case M=3 and m=1), as shown in the
where j is the imaginary unit. For a further description of the fourth step S64 of aligning and adding reference is made to the description of
[0207] As shown in
[0208] Further, as shown in
[0209] The above description is also valid in case M, m, and N have different values.
[0210] Therefore, the DFA according to
[0211] Thus, the DFA of
[0212]
[0213] The transmitter 5 of
[0214] The above description with respect to the transmitter of the second aspect or any of its implementation forms is also valid for the transmitter 5 of
[0215]
[0216] The receiver 6 of
[0217] The above description with respect to the receiver of the third aspect or any of its implementation forms is also valid for the receiver 6 of
[0218]
[0219] The OTS 7 of
[0220] The transmitter 8 may be a transmitter according to the second aspect or any of its implementation forms (such as the transmitter 5 of
[0221] Alternatively or additionally, the receiver 9 may be a receiver according to the third aspect or any of its implementation forms (such as the receiver 6 of
[0222] The above description with respect to the OTS of the fourth aspect or any of its implementation forms is also valid for the OTS 7 of
[0223] The present disclosure has been described in conjunction with various embodiments as examples as well as implementations. However, other variations can be understood and effected by those persons skilled in the art and practicing the claimed invention, from the studies of the drawings, this disclosure and the independent claims. In the claims as well as in the description the word “comprising” does not exclude other elements or steps and the indefinite article “a” or “an” does not exclude a plurality. A single element or other unit may fulfill the functions of several entities or items recited in the claims. The mere fact that certain measures are recited in the mutual different dependent claims does not indicate that a combination of these measures cannot be used in an advantageous implementation.