Joint channel estimation and equalization method and system for OFDM (Orthogonal Frequency Division Multiplexing) system

Abstract

The invention provides a joint channel estimation and equalization method and system for an OFDM (Orthogonal Frequency Division Multiplexing) system, and the method comprises the steps: carrying out the FFT (Fast Fourier Transform) of a received OFDM symbol, and obtaining a frequency domain subcarrier; extracting pilot frequency subcarriers and data subcarriers from the frequency domain subcarriers; performing channel estimation on the pilot frequency subcarrier to obtain a pilot frequency channel response; performing nonlinear compensation on the pilot channel response, and calculating the channel response after nonlinear compensation; performing frequency domain interpolation and time domain interpolation on the channel response after nonlinear compensation to obtain a complete channel matrix; and performing channel equalization on the data subcarriers by using the complete channel matrix to obtain demodulated data symbols. According to the method, the overall division operation times are reduced to WM / P times from WN-WM / P times of a conventional algorithm by advancing matrix inversion operation in channel equalization to channel interpolation; compared with the prior art, the computing speed is increased by (NP-M) / M times, the computing complexity is greatly reduced, consumption of computing resources can be reduced, and the computing speed is increased.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication, in particular, to a joint channel estimation and equalization method and system for OFDM systems. BACKGROUND

[0002] Orthogonal frequency division multiplexing (OFDM) technology has been widely used in 4G, 5G, WIFI and other wireless communication systems due to its high spectral efficiency and anti-multipath interference capability. In OFDM systems, the sending end converts the signal to the time domain by inverse discrete Fourier transform (IDFT) and adds a cyclic prefix (CP), and the receiving end restores the frequency domain signal by discrete Fourier transform (DFT). However, the signal will be affected by channel fading and noise during transmission, so channel estimation and equalization technology is needed to recover the original signal.

[0003] In the prior art, channel estimation usually uses least squares (LS), minimum mean square error (MMSE) or linear minimum mean square error (LMMSE) algorithm. After channel estimation on the pilot subcarrier, these algorithms obtain the channel response of the full frequency band through frequency domain and time domain interpolation, and finally perform channel equalization through zero forcing (ZF) or MMSE algorithm.

[0004] A comb-shaped pilot channel estimation and equalization device and method for OFDM systems are disclosed in patent document No. CN113037664B. The device includes: an input buffer unit for receiving and buffering the effective input data of the OFDM signal; a pilot storage unit for storing local initial pilot symbols; a channel estimation unit for pilot channel response estimation; an IFFT calculation unit for IFFT operation to obtain the time domain impulse response of the wireless channel; an intermediate buffer unit for buffering the first several data of the time domain impulse response; a data preprocessing unit for preprocessing the first several data of the time domain impulse response; an FFT calculation unit for estimating the frequency domain channel response using the preprocessed first several data; a data equalization unit for channel equalization; and an output buffer unit for buffering and outputting the channel equalization result.

[0005] A large number of matrix inversion operations are involved in the channel estimation and equalization process, especially in multiple-input multiple-output (MIMO) systems, the complexity of matrix inversion increases exponentially with the number of antennas, becoming a bottleneck of system performance. Matrix inversion or division operations consume a lot of resources in hardware implementation, and it is difficult to introduce pipeline processing, resulting in limited processing speed. Although the MMSE algorithm has good performance under low signal-to-noise ratio conditions, its computational complexity is high; while the LS algorithm has low complexity, but has large estimation error under low signal-to-noise ratio.

[0006] To address the above issues, existing technologies attempt to reduce complexity by simplifying algorithms or optimizing hardware design, but this often comes at the cost of performance. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide a joint channel estimation and equalization method and system for OFDM systems.

[0008] According to the present invention, a joint channel estimation and equalization method for OFDM systems is provided, the method comprising the following steps:

[0009] Step S1: Perform FFT transformation on the received OFDM symbols to obtain frequency domain subcarriers;

[0010] Step S2: Extract pilot subcarriers and data subcarriers from the frequency domain subcarriers;

[0011] Step S3: Perform channel estimation on the pilot subcarriers to obtain the pilot channel response;

[0012] Step S4: Perform nonlinear compensation on the pilot channel response and calculate the channel response after nonlinear compensation;

[0013] Step S5: Perform frequency domain interpolation and time domain interpolation on the nonlinearly compensated channel response to obtain the complete channel matrix;

[0014] Step S6: Perform channel equalization on the data subcarriers using the complete channel matrix to obtain the demodulated data symbols;

[0015] The nonlinear compensation is achieved through the following formula:

[0016]

[0017] in, H represents the channel estimation compensation for pilot subcarriers. p For channel estimation of pilot subcarriers, P N The average power of the noise is represented by , and * denotes the complex conjugate operation.

[0018] Preferably, the channel estimation in step S3 uses the least squares (LS) method to estimate the pilot channel response, and the specific formula is as follows:

[0019] H p =(R p ·32767·T p +16384·(1+j))>>15

[0020] Among them, H p For pilot channel estimation, R p To receive the pilot subcarrier, Tp To transmit pilot subcarriers; >> indicates a right shift operation. It represents the imaginary unit.

[0021] Preferably, the frequency domain interpolation in step S5 adopts a second-order interpolation method, and the specific formula is as follows:

[0022]

[0023] in, c0 = -(α-1)(α+1),

[0024] K is the pilot subcarrier spacing; These represent the channel estimation compensation for the (m-1), m, and (m+1)th pilot subcarriers of the x-th OFDM symbol, respectively. This represents the channel estimation of the mK+kth subcarrier of the xth OFDM symbol; frequency domain interpolation is performed only on pilot OFDM symbols, i.e., x = nL, where L is the pilot OFDM symbol spacing and n is a non-negative integer.

[0025] Preferably, the time-domain interpolation in step S5 uses linear interpolation, and the specific formula is as follows:

[0026]

[0027] Where l = 0…L-1, and L is the pilot OFDM symbol interval; and Let represent the channel estimates of the y-th subcarrier of the (n-1)L, nL, and nL+l-th OFDM symbols, respectively.

[0028] Preferably, the channel equalization in step S6 is achieved by the following formula:

[0029] S e =(H d *R d +16384*(1+j))>>15

[0030] Among them, R d For data subcarriers, H d S represents the channel response of the corresponding subcarrier. e This represents an estimate of the transmitted signal. It represents the imaginary unit.

[0031] The present invention also provides a joint channel estimation and equalization system for OFDM systems, the system comprising:

[0032] The following modules:

[0033] Module M1: Performs FFT transformation on the received OFDM symbols to obtain frequency domain subcarriers;

[0034] Module M2: Extracts pilot subcarriers and data subcarriers from frequency domain subcarriers;

[0035] Module M3: Performs channel estimation on the pilot subcarriers to obtain the pilot channel response;

[0036] Module M4: Performs nonlinear compensation on the pilot channel response and calculates the channel response after nonlinear compensation;

[0037] Module M5: Performs frequency domain interpolation and time domain interpolation on the nonlinearly compensated channel response to obtain the complete channel matrix;

[0038] Module M6: Performs channel equalization on the data subcarriers using the complete channel matrix to obtain demodulated data symbols;

[0039] The nonlinear compensation is achieved through the following formula:

[0040]

[0041] in, H represents the channel estimation compensation for pilot subcarriers. p For channel estimation of pilot subcarriers, P N The average power of the noise is represented by , and * indicates the complex conjugate transpose operation.

[0042] Preferably, the channel estimation in module M3 uses the least squares (LS) method to estimate the pilot channel response, and the specific formula is as follows:

[0043] H p =(R p *32767·T p +16384·(1+j))>>15

[0044] Among them, H p For pilot channel estimation, R p To receive the pilot subcarrier, T p To transmit pilot subcarriers; >>

[0045] This represents a right shift operation. It represents the imaginary unit.

[0046] Preferably, the frequency domain interpolation in module M5 adopts a second-order interpolation method, and the specific formula is as follows:

[0047]

[0048] in, c0 = -(α-1)(α+1), K is the pilot subcarrier spacing; These represent the channel estimation compensation for the (m-1), m, and (m+1)th pilot subcarriers of the x-th OFDM symbol, respectively. This represents the channel estimation of the mK+kth subcarrier of the xth OFDM symbol; frequency domain interpolation is performed only on pilot OFDM symbols, i.e., x = nL, where L is the pilot OFDM symbol spacing and n is a non-negative integer.

[0049] Preferably, the time-domain interpolation in module M5 uses linear interpolation, with the specific formula as follows:

[0050]

[0051] Where l = 0…L-1, and L is the pilot OFDM symbol interval; and Let represent the channel estimates of the y-th subcarrier of the (n-1)L, nL, and nL+l-th OFDM symbols, respectively.

[0052] Preferably, the channel equalization in module M6 is achieved through the following formula:

[0053] S e =(H d *R d +16384*(1+j))>>15

[0054] Among them, R d For data subcarriers, H d S represents the channel response of the corresponding subcarrier. e This represents an estimate of the transmitted signal. It represents the imaginary unit.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] 1. This invention reduces the total number of division operations from WN-WM / P times in the conventional algorithm to WM / P times by moving the matrix inversion operation in channel equalization before channel interpolation; the operation speed is increased by (NP-M) / M times, which greatly reduces hardware resource consumption and computational latency.

[0057] 2. This invention optimizes the algorithm flow, avoiding complex matrix inversion operations and replacing division operations with simple operations such as shifting and addition, significantly reducing the complexity of hardware implementation. This makes the algorithm more suitable for efficient implementation on hardware platforms such as FPGA or ASIC, while supporting pipelined processing and improving the real-time performance of the system.

[0058] 3. Simulation results under AWGN and LTE EPA channels show that the performance of the present invention is basically unaffected by traditional algorithms. The simulation data verifies that the performance of the present invention in terms of bit error rate and signal-to-noise ratio is comparable to that of traditional algorithms, proving its reliability in practical applications.

[0059] 4. This invention is not only applicable to single-antenna systems, but can also be extended to MIMO systems, demonstrating good versatility. Furthermore, its pilot design and interpolation algorithm can be flexibly adjusted according to specific application scenarios, making it suitable for various wireless communication standards.

[0060] 5. Due to the reduction in computational complexity, this invention reduces the demand for hardware resources, lowers system power consumption and cost, and is particularly suitable for resource-constrained terminal devices or large-scale deployed communication systems. Attached Figure Description

[0061] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0062] Figure 1 This is a schematic diagram of the quasi-static channel of the present invention;

[0063] Figure 2 This is a schematic diagram of the multipath channel frequency domain channel response of the present invention;

[0064] Figure 3 This is a schematic diagram of the burst wireless frame structure of the present invention;

[0065] Figure 4 This is a flowchart of the joint channel estimation and equalization process of the present invention;

[0066] Figure 5 This is a schematic diagram of the FFT and associated rotation of the present invention;

[0067] Figure 6 This is a schematic diagram of channel estimation and interpolation in this invention;

[0068] Figure 7 This is a performance comparison diagram of the present invention under the AWGN channel;

[0069] Figure 8 This is a schematic diagram showing the performance comparison of the present invention under the LTE EPA channel. Detailed Implementation

[0070] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0071] Example 1

[0072] According to the present invention, a joint channel estimation and equalization method for OFDM systems is provided, the method comprising the following steps:

[0073] Step S1: Perform FFT transformation on the received OFDM symbols to obtain frequency domain subcarriers;

[0074] Step S2: Extract pilot subcarriers and data subcarriers from the frequency domain subcarriers;

[0075] Step S3: Perform channel estimation on the pilot subcarriers to obtain the pilot channel response; the channel estimation uses the least squares (LS) method to estimate the pilot channel response, and the specific formula is as follows:

[0076] H p =(R p ·32767·T p +16384·(1+j))>>15

[0077] Among them, H p For pilot channel estimation, R p To receive the pilot subcarrier, T p To transmit pilot subcarriers. >>

[0078] This represents a right shift operation. It represents the imaginary unit.

[0079] Step S4: Perform nonlinear compensation on the pilot channel response and calculate the channel response after nonlinear compensation;

[0080] Step S5: Perform frequency domain interpolation and time domain interpolation on the nonlinearly compensated channel response to obtain the complete channel matrix; the frequency domain interpolation uses a second-order interpolation method, and the specific formula is as follows:

[0081]

[0082] in, c0 = -(α-1)(α+1), K is the pilot subcarrier spacing. These represent the channel estimation compensation for the (m-1), m, and (m+1)th pilot subcarriers of the x-th OFDM symbol, respectively. This represents the channel estimate for the mK+kth subcarrier of the x-th OFDM symbol. Frequency domain interpolation is performed only on pilot OFDM symbols, i.e., x = nL, where L is the pilot OFDM symbol spacing and n is a non-negative integer.

[0083] The time-domain interpolation uses linear interpolation, and the specific formula is as follows:

[0084]

[0085] Where l = 0…L-1, and L is the pilot OFDM symbol spacing. and Let represent the channel estimates of the y-th subcarrier of the (n-1)L, nL, and nL+l-th OFDM symbols, respectively.

[0086] Step S6: Perform channel equalization on the data subcarriers using the complete channel matrix to obtain the demodulated data symbols; channel equalization is achieved using the following formula:

[0087] S e =(H d *R d +16384*(1+j))>>15

[0088] Among them, R d For data subcarriers, H d S represents the channel response of the corresponding subcarrier. e This represents an estimate of the transmitted signal. It represents the imaginary unit.

[0089] The nonlinear compensation is achieved through the following formula:

[0090]

[0091] in, H represents the channel estimation compensation for pilot subcarriers. p For channel estimation of pilot subcarriers, P N The average power of the noise is represented by , and * indicates the complex conjugate transpose operation.

[0092] The present invention also provides a joint channel estimation and equalization system for OFDM systems, wherein the system is used for...

[0093] The joint channel estimation and equalization system for OFDM systems can be implemented by executing the procedural steps of the joint channel estimation and equalization method for OFDM systems. That is, those skilled in the art can understand the joint channel estimation and equalization method for OFDM systems as a preferred implementation of the joint channel estimation and equalization system for OFDM systems.

[0094] Example 2

[0095] The present invention also provides a joint channel estimation and equalization system for OFDM systems, the system comprising:

[0096] The following modules:

[0097] Module M1: Performs FFT transformation on the received OFDM symbols to obtain frequency domain subcarriers;

[0098] Module M2: Extracts pilot subcarriers and data subcarriers from frequency domain subcarriers;

[0099] Module M3: Performs channel estimation on the pilot subcarriers to obtain the pilot channel response; the channel estimation uses the least squares (LS) method to estimate the pilot channel response, and the specific formula is as follows:

[0100] H p =(R p ·32767·T p +16384·(1+j))>>15

[0101] Among them, H p For pilot channel estimation, R p To receive the pilot subcarrier, T p To transmit pilot subcarriers. >>

[0102] This represents a right shift operation. It represents the imaginary unit.

[0103] Module M4: Performs nonlinear compensation on the pilot channel response and calculates the channel response after nonlinear compensation;

[0104] Module M5: Performs frequency domain interpolation and time domain interpolation on the nonlinearly compensated channel response to obtain the complete channel matrix; the frequency domain interpolation uses a second-order interpolation method, and the specific formula is as follows:

[0105]

[0106] in, c0 = -(α-1)(α+1), K is the pilot subcarrier spacing. These represent the channel estimation compensation for the (m-1), m, and (m+1)th pilot subcarriers of the x-th OFDM symbol, respectively. This represents the channel estimate for the mK+kth subcarrier of the x-th OFDM symbol. Frequency domain interpolation is performed only on pilot OFDM symbols, i.e., x = nL, where L is the pilot OFDM symbol spacing and n is a non-negative integer.

[0107] The time-domain interpolation uses linear interpolation, and the specific formula is as follows:

[0108]

[0109] Where l = 0…L-1, and L is the pilot OFDM symbol spacing. and Let represent the channel estimates of the y-th subcarrier of the (n-1)L, nL, and nL+l-th OFDM symbols, respectively.

[0110] Module M6: Performs channel equalization on the data subcarriers using the complete channel matrix to obtain demodulated data symbols; channel equalization is achieved through the following formula:

[0111] S e =(H d *R d +16384*(1+j))>>15

[0112] Among them, R d For data subcarriers, H d S represents the channel response of the corresponding subcarrier. e This represents an estimate of the transmitted signal. It represents the imaginary unit.

[0113] The nonlinear compensation is achieved through the following formula:

[0114]

[0115] in, H represents the channel estimation compensation for pilot subcarriers. p For channel estimation of pilot subcarriers, P N The average power of the noise is represented by , and * indicates the complex conjugate transpose operation.

[0116] Example 3

[0117] This invention combines channel estimation and channel equalization: after channel estimation, a nonlinear compensation module is added, eliminating the need for matrix inversion operations during channel equalization. This significantly reduces computational complexity with minimal performance loss.

[0118] Wireless signals experience channel fading as they travel through a channel. Fading is categorized into large-scale fading and small-scale fading. Large-scale fading is caused by signal attenuation over long distances and complete or partial line-of-sight (LoS) path loss due to significant obstacles (relative to the wireless signal wavelength) in the propagation path. Small-scale fading refers to rapid fluctuations occurring within a short timeframe (relative to the wireless signal period) or over a short distance (relative to the wireless signal wavelength). These fluctuations are caused by the superposition of transmitted signals arriving through different propagation paths; this phenomenon is called multipath propagation.

[0119] Consider a quasi-static scenario, such as Figure 1As shown, if the transmitter, receiver, and reflector remain static during the signal transmission period, the received signal travels a distance of p0 and a distance of p1+p2, respectively, with time delays of τ0 and τ1, and path losses (including phase changes) of g0 and g1, respectively. Therefore, the received signal is:

[0120]

[0121] Within an OFDM symbol, if the transmitted sequence consists of independent and uncorrelated random signals, then It is still a random variable. This is multipath interference.

[0122] Frequency response of received signal:

[0123]

[0124] The LS estimation of the frequency domain channel is as follows:

[0125]

[0126] Within a single OFDM radio frame, the multipath delay τ1-τ0 can be approximated as constant. Therefore, the channel coefficient H(f) is a function of frequency and independent of time. Thus, within an OFDM symbol, frequency domain interpolation can be performed to estimate the channel coefficient for the entire frequency band. For one or more adjacent OFDM symbols, since the multipath delay τ1-τ0 remains constant, time domain interpolation can be used to estimate the channel coefficient for the entire radio frame.

[0127] Furthermore, since the channel coefficient H(f) is a function of frequency, then H H H+σ 2 I is independent of time, therefore (H) in channel equalization can be used to... H H+σ 2 I) -1 Moving the operation before channel interpolation reduces the overall matrix inversion or division computation to approximately 1 / DP, where D is the interval between frequency domain pilot symbols and P is the interval between time domain pilot symbols. Taking LTE as an example, a radio subframe has 14 symbols. Pilots are inserted into OFDM symbols 0, 4, 7, and 11, with a pilot subcarrier interval of 6. The overall division computation is then approximately reduced to 4 / (14×6) = 1 / 21. This invention refers to this process as "nonlinear compensation."

[0128] like Figure 3This is a structure for an OFDM burst radio frame. The chip rate is 23.04 M / s, the FFT number is 1024, and the CP length is 64. A burst frame is divided into four parts: AGC, S, C, and D. AGC is used for automatic gain control, using an m-sequence, occupying 80 subcarriers (1.8 MHz) in the frequency domain and 2 OFDM symbols in the time domain; S is used for synchronization, also using an m-sequence length, occupying 80 subcarriers (1.8 MHz) in the frequency domain and 1 OFDM symbol in the time domain; C carries control information, occupying 80 or 160 subcarriers (1.8 MHz or 3.6 MHz) in the frequency domain and 1 OFDM symbol in the time domain; D carries data, the length and bandwidth of which are indicated by the control segment, potentially occupying 80, 160, 320, or 640 subcarriers in the frequency domain and 0–255 OFDM symbols in the time domain.

[0129] Assuming the CP length is L, the number of FFT points is N, and the number of effective subcarriers is M, the technical solution of this invention is detailed below:

[0130] FFT: The time-domain code slice rn (n=0,1...L+N-1) of the OFDM symbol is taken as (rL / 2,rL / 2+1...rL / 2+N-1) and FFT is performed to obtain the frequency-domain subcarrier Rf (f=0,1...N-1).

[0131] Digital AGC: Perform digital AGC on the above subcarrier R to limit the average power to 224~228, resulting in R'f. Then the absolute value of the subcarrier is between 212~214.

[0132] Phase rotation: The rotation factor is Rotf = round(32767·e jπLf / N ), j represents the complex unit, and the calculation method is: C = (R ' f Rot f +16384·(1+j))>>15, round means rounding, >> means right shift operation. In this way, inter-symbol interference caused by multipath transmission can be overcome.

[0133] Subcarrier extraction: Obtain the pilot subcarrier Rp and the data subcarrier Rd.

[0134] Channel estimation: then H p =(R p ·32767·T p +16384·(1+j))>>15,T p Indicates the transmission pilot subcarrier, 32767·T p The calculation is expected to be completed and stored in memory as a whole. Then, the virtual subcarriers are further estimated:

[0135] Noise estimation: P N =∑(N i ) 2 .

[0136] Channel nonlinearity compensation:

[0137] Channel frequency domain interpolation: Using second-order interpolation, with a pilot spacing of K, then... in, c0 = -(α-1)(α+1), represents the channel response estimates of the (m-1), m, and (m+1)th pilot subcarriers of the x-th OFDM symbol after nonlinear compensation. This represents the channel response estimate for the mK+kth subcarrier of the x-th OFDM symbol. Frequency domain interpolation is performed only on pilot OFDM symbols, i.e., x = nL, where L is the pilot OFDM symbol spacing and n is a non-negative integer.

[0138] Channel time-domain interpolation: linear interpolation method is used. Where l = 0…L-1, and L is the pilot OFDM symbol spacing. and Let represent the channel response estimates of the y-th subcarrier of the (n-1)L, nL, and nL+l-th OFDM symbols, respectively.

[0139] Channel equalization: S = (H d *R d +16384*(1+j))>>15.

[0140] This invention can significantly reduce complexity without much loss of performance. If the number of subcarriers in the bandwidth is W, the pilot subcarrier spacing is P, the total number of OFDM symbols is N, and the total number of pilot symbols is M, then the number of divisions (division for single antenna and matrix inversion for multi-antenna MIMO) in the conventional linear interpolation + equalization algorithm is: WN-WM / P, while the number of divisions in the improved algorithm is: WM / P. In comparison, the operation speed is improved by (NP-M) / M times.

[0141] To verify the effectiveness of this invention, simulations were performed comparing the conventional LS estimation + MMSE equalization algorithm (hereinafter referred to as the conventional algorithm) and the scheme of this invention (hereinafter referred to as the improved scheme). The pilot patterns are shown below. Figure 6 As shown, other parameters are listed in Table 1. Simulation results... Figure 7 and Figure 8As can be seen, there is basically no performance loss under AWGN channel and LTEEPA (Extended Pedestrian A model) channel, and the number of divisions is reduced to 1 / 12.

[0142] Table 1 Simulation Parameters

[0143]

[0144]

[0145] in:

[0146] AWGN: Additive White Gaussian Noise;

[0147] CP: Cyclic Prefix;

[0148] DFT: Discrete Fourier Transform;

[0149] OFDM: Orthogonal Frequency Division Multiplexing;

[0150] EPA: Extended Pedestrian A model;

[0151] FFT: Fast Fourier Transform;

[0152] IDFT: Inverse Discrete Fourier Transform;

[0153] IFFT: Inverse Fast Fourier Transform;

[0154] LS: Least Squares;

[0155] LMMSE: Linear Minimum Mean Square Error;

[0156] MMSE: Minimum Mean Square Error;

[0157] PSK: phase-shift keying;

[0158] QAM: Quadrature Amplitude Modulation;

[0159] ZF: Zero Forcing.

[0160] Those skilled in the art can understand this embodiment as a more specific description of Embodiment 1 and Embodiment 2.

[0161] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0162] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for joint channel estimation and equalization for OFDM systems, characterized in that, The method comprises the following steps: Step S1: performing FFT transformation on the received OFDM symbol to obtain a frequency domain subcarrier; Step S2: extracting a pilot subcarrier and a data subcarrier from the frequency domain subcarrier; Step S3: performing channel estimation on the pilot subcarrier to obtain a pilot channel response; Step S4: performing nonlinear compensation on the pilot channel response to calculate a nonlinearly compensated channel response; Step S5: performing frequency domain interpolation and time domain interpolation on the nonlinearly compensated channel response to obtain a complete channel matrix; Step S6: performing channel equalization on the data subcarrier by using the complete channel matrix to obtain a demodulated data symbol; The nonlinear compensation is realized by the following formula: wherein denotes the channel estimation compensation of the pilot subcarriers, H p is the channel estimation of the pilot subcarriers, P N is the average power of the noise, * denotes the complex conjugate operation.

2. The method for joint channel estimation and equalization for OFDM systems according to claim 1, characterized in that, The channel estimation in the step S3 adopts a least square method LS to perform pilot channel response estimation, and the specific formula is: H p = (R p · 32767 · T p + 16384 · (1 + j)) » 15 where H p is the pilot channel estimation, R p is the received pilot subcarrier, T p is the transmitted pilot subcarrier; >> denotes right shift operation, denotes the imaginary unit.

3. The method for joint channel estimation and equalization for OFDM systems of claim 1, wherein, The frequency domain interpolation in the step S5 adopts a second-order interpolation method, and the specific formula is: wherein, c0= -(a - 1)(a + 1), k = 0...K - 1, K is the pilot subcarrier spacing; respectively represent the channel estimation compensation of the m-1th, mth and m+1th pilot subcarriers of the xth OFDM symbol; represents the channel estimation of the mK + kth subcarrier of the xth OFDM symbol; the frequency domain interpolation is only performed on the pilot OFDM symbols, i.e. x = nL, L is the pilot OFDM symbol spacing, and n is a non-negative integer.

4. The method for joint channel estimation and equalization for OFDM systems of claim 1, wherein, The time domain interpolation in the step S5 adopts a linear interpolation method, and the specific formula is: where l = 0...L-l, L is the pilot OFDM symbol interval; and denote the channel estimates of the yth subcarrier of the (n-1)Lth, nth, and nth+Lth OFDM symbols, respectively.

5. The method for joint channel estimation and equalization for OFDM systems of claim 1, wherein, The channel equalization in the step S6 is realized by the following formula: S e = (H d *R d + 16384 * (1 + j) ) » 15 where R d is a data subcarrier, H d represents the channel response for the corresponding subcarrier, S e represents an estimate of the transmitted signal, represents the imaginary unit.

6. A joint channel estimation and equalization system for an OFDM system, characterized by, The system comprises the following modules: Module M1: performing FFT transformation on the received OFDM symbol to obtain a frequency domain subcarrier; Module M2: extracting a pilot subcarrier and a data subcarrier from the frequency domain subcarrier; Module M3: performing channel estimation on the pilot subcarrier to obtain a pilot channel response; Module M4: performing nonlinear compensation on the pilot channel response to calculate a nonlinearly compensated channel response; Module M5: performing frequency domain interpolation and time domain interpolation on the nonlinearly compensated channel response to obtain a complete channel matrix; Module M6: performing channel equalization on the data subcarrier by using the complete channel matrix to obtain a demodulated data symbol; The nonlinear compensation is realized by the following formula: wherein denotes the channel estimation compensation of the pilot subcarriers, H p is the channel estimation of the pilot subcarriers, P N is the average power of the noise, * denotes the complex conjugate transpose operation.

7. The joint channel estimation and equalization system for OFDM systems of claim 6, wherein, The channel estimation in the module M3 adopts a least square method LS to perform pilot channel response estimation, and the specific formula is: H p = (R p · 32767 · T p + 16384 · (1 + j)) » 15 where H p is the pilot channel estimation, R p is the received pilot subcarrier, T p is the transmitted pilot subcarrier; and >> denotes a right shift operation, denotes the imaginary unit.

8. The joint channel estimation and equalization system for OFDM systems of claim 6, wherein, The frequency domain interpolation in the module M5 adopts a second-order interpolation method, and the specific formula is: wherein, c0= -(a - 1)(a + 1), k = 0...K - 1, K is the pilot subcarrier spacing; respectively represent the channel estimation compensation of the m-1th, mth and m+1th pilot subcarriers of the xth OFDM symbol; represents the channel estimation of the mK + kth subcarrier of the xth OFDM symbol; the frequency domain interpolation is only performed on the pilot OFDM symbols, i.e. x = nL, L is the pilot OFDM symbol spacing, and n is a non-negative integer.

9. The joint channel estimation and equalization system for OFDM systems according to claim 6, characterized in that, The time domain interpolation in the module M5 adopts a linear interpolation method, and the specific formula is: where l = 0...L-1, L is the pilot OFDM symbol interval; and denote the channel estimates of the yth subcarrier of the (n-1)Lth, nth, and nth+Lth OFDM symbols, respectively.

10. The joint channel estimation and equalization system for OFDM systems according to claim 6, wherein, The channel equalization in the module M6 is realized by the following formula: S e = (H d *R d + 16384 * (1 + j) ) » 15 where R d is a data subcarrier, H d represents the channel response for the corresponding subcarrier, S e represents an estimate of the transmitted signal, represents the imaginary unit.

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