CN109639610B - Millimeter wave communication-oriented sampling frequency offset optimization method and corresponding transmitter - Google Patents
Millimeter wave communication-oriented sampling frequency offset optimization method and corresponding transmitter Download PDFInfo
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Abstract
The invention discloses a sampling frequency offset optimization method and a corresponding transmitter. The method comprises the following steps: different transmitting powers are distributed on different pilot frequency sub-carriers, then a random sequence is generated, and the amplitude of each element in the sequence is set according to the distributed powers, so that the random sequence is used as a synchronous signal of sampling frequency offset. On the premise of keeping the pilot frequency overhead unchanged, the invention improves the estimation precision of the receiving end on the sampling frequency offset by the optimal synchronous signal design. Simulation experiments show that the performance of the synchronization signal provided by the invention is superior to that of the traditional synchronization signal in all possible sampling frequency deviation ranges of a millimeter wave communication system.
Description
Technical Field
The invention relates to a sampling frequency offset optimization method, in particular to a method for improving the estimation precision of sampling frequency offset through optimal synchronous signal design in millimeter wave communication, and also relates to a millimeter wave communication system transmitter adopting the sampling frequency offset optimization method, belonging to the technical field of wireless communication.
Background
Millimeter wave communication mainly utilizes frequency band communication with millimeter level wavelength, namely 30-300GHz frequency band. Relevant research concludes that the millimeter wave communication system can reach 25 times of the communication capacity of the existing LTE system. This is difficult to achieve with other prior art techniques. Therefore, millimeter wave communication technology attracts more and more attention of manufacturers, and is now a popular research direction in 5G communication systems.
Compared with the traditional communication system, the millimeter wave communication system has a higher working frequency band, and the channel characteristics are completely different from the traditional frequency band below 3GHz, for example, the millimeter wave communication system has the characteristics of higher path loss, sensitivity to shielding effect, stronger sparsity of a channel, larger change of channel fading characteristics in different environments and the like. In addition, the system bandwidth of the millimeter wave communication system is greatly increased. For example, the basic bandwidth of a conventional communication system such as an LTE system is only 20MHz, while the system bandwidth of a millimeter wave communication system can reach 1GHz in the related technical literature, and even considered as 5 GHz. In order to effectively solve the problems caused by the new characteristics, a set of physical layer signal processing mechanisms specially aiming at the millimeter wave communication system needs to be redesigned to realize functions such as synchronization, channel estimation, equalization and the like.
In the millimeter wave communication system, the strength of the received signal is much lower than that of the conventional frequency band below 3 GHz. This makes the existing sampling frequency offset estimation algorithm not directly usable in the millimeter wave system. On the other hand, the influence of the sampling frequency offset on the communication system becomes larger as the system bandwidth increases, so that the influence on the millimeter wave communication system is larger than that on the conventional communication system. Therefore, it is necessary to design a new sampling frequency offset estimation algorithm specifically for the millimeter wave communication system to reduce the influence of the sampling frequency offset on the system performance.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a sampling frequency offset optimization method facing millimeter wave communication.
Another technical problem to be solved by the present invention is to provide a transmitter of a millimeter wave communication system using the sampling frequency offset optimization method.
In order to achieve the purpose, the invention adopts the following technical scheme:
according to a first aspect of the embodiments of the present invention, there is provided a sampling frequency offset optimization method, including the following steps:
allocating different transmitting power on different pilot frequency sub-carriers; wherein,
let P (i)k) Represents the pilot subcarrier ikGenerating a random sequence s (1), s (2) of length K, s (K); wherein the amplitude of each element s (k) is 1 and the phase is one at [0,2 π]Random numbers are uniformly distributed among the K is a positive integer;
the synchronization signal generated based on the random sequence is:
wherein preferably, when the subcarrier index is 1,2, … N, the pilot subcarrier ikThe power scaling factor above is:
wherein preferably, when the subcarrier index is 0,1, … N-1, the pilot subcarrier ikThe power scaling factor above is:
wherein preferably, when the subcarrier index is-N/2, …,0, … N/2-1, the pilot subcarrier ikThe power scaling factor above is:
where N is the total number of subcarriers, I ═ I1,i2,…,iKDenotes indexes of all pilot subcarriers, and K denotes the number of pilot subcarriers.
Wherein preferably the actual transmit power P (i) on each pilot subcarrier is determined by the following formulak)：
Wherein the method is preferably used in a wireless communication system based on OFDM technology.
Preferably, the wireless communication system is a millimeter wave communication system.
According to a second aspect of the embodiments of the present invention, a millimeter wave communication system transmitter is provided, including a modulation module, a synchronization signal module, an IFFT module, a digital-to-analog conversion module, and an up-conversion module, where the synchronization signal module allocates different transmission powers on different pilot subcarriers by using the above sampling frequency offset optimization method, and then generates a random sequence and sets the amplitudes of each element in the sequence according to the allocated powers, so as to use the random sequence as a synchronization signal of sampling frequency offset.
Compared with the prior art, the sampling frequency offset optimization method provided by the invention optimizes the synchronous signals by optimally distributing the power of the synchronous signals on each pilot frequency subcarrier on the premise of keeping the original pilot frequency overhead unchanged, thereby improving the estimation precision of the receiving end on the sampling frequency offset. Simulation experiments show that the performance of the synchronization signal provided by the invention is superior to that of the traditional synchronization signal in all possible sampling frequency deviation ranges of a millimeter wave communication system.
Drawings
FIG. 1 is a diagram illustrating the relationship between analog-to-digital conversion and sampling frequency offset;
FIG. 2 is a schematic diagram of phase rotation caused by sampling frequency offset;
FIG. 3 is a diagram illustrating a structure of a synchronization signal in the prior art;
FIG. 4 is a graph comparing the mean square error performance of the optimal synchronization signal with the conventional synchronization signal for different SNR;
FIG. 5 is a graph showing a comparison of mean square error performance of an optimal synchronization signal with a conventional synchronization signal at different sampling frequency offsets;
fig. 6 is a schematic structural diagram of a millimeter wave communication system transmitter according to an embodiment of the present invention.
Detailed Description
The technical scheme of the invention is explained in detail in the following by combining the drawings and the specific embodiment.
The Orthogonal Frequency Division Multiplexing (OFDM) technique has many advantages such as high spectrum efficiency, flexible resource allocation, and the like. Particularly, in a broadband communication system, OFDM can better resist frequency selective fading, and thus is widely used in a practical communication system. The millimeter wave communication system is very suitable for adopting the OFDM technology due to the large system bandwidth.
However, an important drawback of the OFDM technique is that the synchronization accuracy of the sampling frequency offset is required to be high. The concrete description is as follows: in the existing OFDM technology, digital signal processing is used inside the receiver, and the actual signal can only be propagated in the form of analog signal in the wireless channel. Therefore, the receiver first needs to convert the analog signal into a digital signal through an analog-to-digital converter (ADC), as shown in fig. 1.
In the analog-to-digital conversion process, the ADC samples at regular intervals with a certain period. This sampling period is typically controlled by a crystal oscillator. In practice, due to the instability and temperature drift of the crystal oscillator itself, the sampling period of the ADC may not completely coincide with the theoretical design value, and thus a sampling frequency offset is formed. As can be seen from fig. 1, if the actual sampling period is smaller than the designed value, the sampling point will be located more and more forward due to the cumulative effect of the sampling frequency offset, thereby causing the FFT (fast fourier transform) window to drift. It is even possible to have one more sample point if not corrected. If the actual sampling period is larger than the designed value, one sampling point is omitted after long-term accumulation. In addition, the orthogonality of the OFDM technique is obtained in the case where the actual sampling period completely coincides with the theoretical design value. If sampling frequency offset occurs, the orthogonality of the system is broken, and inter-subcarrier interference (ICI) is caused.
In addition, the sampling frequency offset introduces a phase rotation to the received signal, as shown in the following equation:
wherein, Ym(i) Is the received signal on the ith subcarrier of the mth OFDM symbol, N is the number of subcarriers, Nb＝N+Ng，NgLength of cyclic prefix, Δ fSFor sampling frequency offsets, H (i) is the channel, Xm(i) For the transmitted signal on the ith subcarrier of the mth OFDM symbol, Wm(i) ICI as well as noise are indicated, N, m being positive integers. As can be seen from fig. 2, the phase rotation caused by the sampling frequency offset increases not only linearly with the increase of time, but also linearly with the increase of the subcarrier frequency. This means that: the millimeter wave communication system has a large system bandwidth, and the influence of sampling frequency offset is particularly serious.
In order to reduce the performance degradation of the wireless communication system caused by the sampling frequency offset as much as possible, the sampling frequency offset needs to be estimated and compensated by using a sampling frequency offset estimation algorithm. However, in the existing millimeter wave communication system, due to the large path loss, the strength of the received signal is about 20 to 25dB lower than that of the frequency band below 3GHz, which is far beyond the capability of the existing sampling frequency offset estimation algorithm. Therefore, there is a need to redesign sampling frequency offset estimation algorithms that can operate at lower signal-to-noise ratios. In order to improve the estimation performance of the sampling frequency offset, an optimal design scheme of the synchronization signal at the transmitting end needs to be considered.
In the prior art, when estimating the sampling frequency offset, the synchronization signal at the transmitting end always uses the same pilot frequency structure. As shown in fig. 3: in two adjacent OFDM symbols, some subcarriers are selected as pilot subcarriers (such as subcarrier i in FIG. 3)n,im) Then, the same pilot signal is sent at the same subcarrier position of two OFDM symbols (the pilot signals on different subcarriers may be the same or different), the amplitudes of all pilot signals are kept the same, all pilot signals are the same
(i.e. signal s in FIG. 3)n,smAre all PSK modulated. ) It is noted that due to the strong non-linearity of the sampling frequency offset, the estimation algorithm usually requires at least 2 symbol periods to complete, and further requires the channel to be in these two OFDM symbol periodsThere is no change in the interval. The reason why two adjacent OFDM symbols are used here is that the carrier frequency in the millimeter wave communication system is high, and the doppler shift caused by the same moving speed is much higher than the frequency band below 3GHz, that is, the speed of channel change in millimeter wave communication is much higher than the frequency band below 3 GHz. Both theoretical and experimental results indicate that such synchronization signals are not theoretically optimal synchronization signal designs.
By deeply researching the technical characteristics of a millimeter wave communication system, the sampling frequency offset optimization method optimizes the synchronous signals by optimally distributing the power of the synchronous signals on each pilot frequency subcarrier on the premise of keeping the original pilot frequency overhead unchanged, thereby improving the estimation precision of the receiving end on the sampling frequency offset. This will be explained in detail below.
First, it can be seen visually in fig. 2: the phase rotation caused by the sampling frequency offset is proportional to the index of the subcarrier, i.e.
Wherein,
representing the phase rotation, Δ f, on the subcarrier iSRepresenting the sampling frequency offset, α is a coefficient having a constant value. The estimation of the sampling frequency offset is mainly carried out by rotating the phase
To obtain a sampling frequency offset Δ fSI.e. by
It should be noted that the above formula (2) is only an expression obtained by greatly simplifying the related sampling frequency offset estimation algorithm to illustrate the technical idea of the present invention, and is not the original estimation algorithm. The detailed mathematical derivation of the sampling frequency offset optimization estimation algorithm can be found in the Joint maximum likelihood estimation of carrier and sampling frequency offsets for OFDM systems of y.h.kim and j.h.lee (published in IEEE transactions, broadcast, vol.57, pp.277-283, June2011.), in the all-complex ML estimation for carrier and sampling frequency offsets in OFDM systems of x.wang and b.hu (published in IEEE Communications Letters, vol.18, pp.503-506, mar.2014.), and in the Low complexity estimation of carrier and sampling frequency offsets in OFDM systems of y.music and r.bor (published in OFDM frequencies, 9, published in OFDM: wo.10, wo.26-506, dar.2014.), in the y.music and r.bor.
Since the noise power on different sub-carriers is equal, on each sub-carrier
Is the same, i.e.
The same is true. However, the index i of different subcarriers is different. If reduced to the sampling frequency offset, the Δ f contained on different sub-carriersSThe accuracy of the information of (a) is not the same. According to the Statistical Signal Processing Theory (see S.M. Kay's monograph of fundamental Signal Processing: Estimation Theory, Prentice Hall,1993.ISBN: 978-.
Based on the above analysis thought, the sampling frequency offset optimization method provided by the invention comprises the following implementation steps:
step 1) calculating power proportion coefficients on each pilot frequency subcarrier.
In the prior art, various subcarrier indexing approaches may be used, and the following classification is discussed. Let N denote the total number of subcarriers in the system, I ═ I1,i2,…,iKDenotes indexes of all pilot subcarriers, and K denotes the number of pilot subcarriers.
(1) If the subcarrier index of the OFDM system is 1,2, … N, the pilot subcarrier ikHas a power proportionality coefficient of
(2) If the subcarrier index of the OFDM system is 0,1, … N-1, then the pilot subcarrier ikHas a power proportionality coefficient of
(3) If the subcarrier index of the OFDM system is-N/2, …,0, … N/2-1, then the pilot subcarrier ikHas a power proportionality coefficient of
Step 2) determining the actual transmission power P (i) on each pilot subcarrierk)。
And 3) generating a random sequence s (1), s (2) with the length of K. Wherein the amplitude of each element s (k) is 1 and the phase is a random number uniformly distributed between 0 and 2 pi. The final synchronization signal is:
thus, the design of the synchronous signal provided by the invention is finished.
It can be seen from the above implementation steps that the pilot signal used in the present invention is exactly the same as the pilot signal of the conventional synchronization signal, so that no additional pilot overhead is added. Furthermore, the total transmission power of all pilot signals in the present invention is:
this is also the same as the total power of a conventional synchronization signal.
It is noted that in the ML estimation algorithm (see the article "a low-complexity ML estimators for carriers and sampling frequency offsets in OFDM systems", published in IEEE Communications Letters, vol.18, pp.503-506, mar.2014.), only the index values of the respective pilot subcarriers and the received signals on the corresponding pilot subcarriers are required, and the values of the pilot signals do not need to be known. Therefore, it is not necessary for the receiving end to know what kind of synchronization signal is specifically used by the transmitting end. In other words, the operation of the receiving end is the same whether the transmitting end uses the conventional synchronization signal or the optimal synchronization signal provided by the present invention.
In order to verify the performance of the optimal synchronization signal provided by the present invention, the inventors performed monte carlo simulation experiments. Specifically, the inventor adopts a set of general simulation environment settings for sampling frequency offset, and examples of main simulation parameters are shown in table 1. The receiver uses the optimal ML estimation algorithm, see article A low-complexity ML estimator for carrier and sampling frequency offsets in OFDM systems of X.Wang and B.Hu (IEEE Communications Letters, vol.18, pp.503-506, Mar.2014.), Y.H.Kim and J.H.Lee. journal maximum frequency estimation of carrier and sampling frequency offsets for OFDM systems (IEEE transactions Broadcast, vol.57, pp.277-2011.).
Table 1 example of major simulation parameters
| N | 64 |
| Nb | 80 |
| K | 62 |
| ΔfS | 112ppm |
| channel power delay profile | exponential |
| channel fading | Rayleigh |
Fig. 4 compares the mean square error performance of the optimal synchronization signal provided by the present invention with the conventional synchronization signal at different signal-to-noise ratios. Since the ML estimation algorithm is a theoretically optimal estimation, the estimated performance obtained by simulation directly represents the performance of the corresponding synchronization signal. As can be seen from fig. 4, the optimal synchronization signal provided by the present invention can effectively improve the estimation performance of the sampling frequency offset by 1.3 dB.
Fig. 5 compares the mean square error performance of the optimal synchronization signal provided by the present invention with the conventional synchronization signal under different sampling frequency offsets. As can be seen from fig. 5, the performance of the optimal synchronization signal provided by the present invention is superior to the conventional synchronization signal in all possible sampling frequency offset ranges encountered in the millimeter wave communication system.
It should be noted that the optimal synchronization signal provided by the present invention does not modify the position of the original pilot signal. Therefore, the technical scheme of the invention can be used for a millimeter wave communication system and can be further extended to all wireless communication systems using OFDM technology, such as a 4G/5G communication system.
The embodiment of the invention also provides a millimeter wave communication system transmitter. As shown in fig. 6, the transmitter includes a modulation module, a synchronization signal module, an IFFT module, a digital-to-analog conversion module, and an up-conversion module, wherein data to be transmitted first enters the modulation module for modulation, and the modulated data and the synchronization signal provided by the synchronization signal module enter the IFFT module together. In the IFFT module, inverse fast fourier transform is performed and CP (cyclic prefix) is added, and then sent to the digital-to-analog conversion module to be converted into an analog signal. The analog signal is sent to the up-conversion module and is transmitted outside through the antenna. In the transmitter shown in fig. 6, the synchronization signal module uses the optimized sampling frequency offset synchronization signal to allocate different transmission powers on different pilot subcarriers, and then generates a random sequence and sets the amplitude of each element in the sequence according to the allocated power, so as to serve as the synchronization signal of the sampling frequency offset. The synchronization signal module employing the optimized sampling frequency offset synchronization signal may exist in the millimeter wave communication system transmitter in the form of an ASIC (application specific integrated circuit) chip.
The millimeter wave communication-oriented sampling frequency offset optimization method and the corresponding transmitter provided by the invention are explained in detail above. Any obvious modifications to the invention, which would occur to those skilled in the art, without departing from the true spirit of the invention, would constitute a violation of the patent rights of the invention and would carry a corresponding legal responsibility.
Claims (4)
1. A sampling frequency offset optimization method is characterized in that different transmitting powers are distributed on different pilot frequency sub-carriers; wherein,
let P (i)k) Represents the pilot subcarrier ikGenerating a random sequence s (1), s (2) of length K, s (K); wherein the amplitude of each element s (k) is 1 and the phase is one at [0,2 π]Random numbers uniformly distributed among them;
the synchronization signal generated based on the random sequence is:
pilot subcarrier i when subcarrier index is 1,2, … NkThe power scaling factor above is:
when the subcarrier index is 0,1, … N-1, pilot subcarrier ikThe power scaling factor above is:
when the subcarrier index is-N/2, …,0, … N/2-1, the pilot subcarrier ikThe power scaling factor above is:
determining each pilot subcarrier i by the following formulakActual transmission power P (i)k)：
Where N is the total number of subcarriers, I ═ I1,i2,…,iKDenotes indexes of all pilot subcarriers, and K denotes the number of pilot subcarriers.
2. The method of sampling frequency offset optimization according to claim 1, wherein said method is used in a wireless communication system based on OFDM technology.
3. The method of sampling frequency offset optimization according to claim 2, wherein said wireless communication system is a millimeter wave communication system.
4. A millimeter wave communication system transmitter comprises a modulation module, a synchronous signal module, an IFFT module, a digital-to-analog conversion module and an up-conversion module, and is characterized in that the synchronous signal module adopts the sampling frequency offset optimization method of claim 1 to distribute different transmitting powers on different pilot frequency sub-carriers, then a random sequence is generated and the amplitude of each element in the sequence is set according to the distributed powers, and the random sequence is used as a synchronous signal of sampling frequency offset.
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