CN102195672A - OFDM (Orthogonal Frequency Division Multiplexing) system inter-cell interference elimination method based on IDMA (Interleave-Division Mutiple-Access) - Google Patents

Abstract

The invention provides an OFDM (Orthogonal Frequency Division Multiplexing) system inter-cell interference elimination method based on IDMA (Interleave-Division Mutiple-Access), which comprises the following steps of: distinguishing different cell base station transmitters by configurations of different interleavers; and classifying all the base stations except a T-BS (Target cell Base Station) into an S-BS (Strong interference Base Station) and a W-BS (Weak interference Base Station) according to strength of interference signals by a mobile user receiver, wherein a signal of the W-BS is processed as a gaussian noise, a signal of the T-BS and a signal of the S-BS are detected in iteration, therefore interference outside the T-BS can be suppressed and estimate data of the T-BS can be obtained. The OFDM system inter-cell interference elimination method based on IDMA, provided by the invention, has the advantage of excellent interference suppression performance gained from iteration.

Description

OFDM system inter-cell interference elimination method based on IDMA

Technical Field

The invention relates to a technology for suppressing inter-cell interference of a mobile communication system, in particular to an OFDM system inter-cell interference elimination method based on IDMA.

Background

Inter-cell interference is an inherent problem of cellular mobile communication systems. The Orthogonal Frequency Division Multiplexing (OFDM) technology reduces the interference in a cell to be low, and the interference between cells becomes the main interference which influences the performance of a system. At present, some researches on the inter-cell interference suppression technology of the OFDM system are carried out at home and abroad, the domestic researches on the inter-cell interference suppression technology are concentrated on interference coordination, and the researches on the interference cancellation technology are relatively few. The invention focuses on an IDMA-based interference elimination method.

An IDMA (Interleave-Division Multiple Access) is a Multiple Access communication mode, which adopts low-code rate coding and uses different interleavers to distinguish different users, thus not only saving special spread spectrum sequence, but also greatly reducing complexity of multi-user detection by an iterative signal detection method, thereby improving system performance. At present, the domestic patents related to the IDMA technology are few, and no patent for eliminating the inter-cell interference by applying the IDMA technology is involved.

In the cellular network model of the OFDM system shown in fig. 1, among signals of cell base stations that can be received by a mobile subscriber, the signal strength of a cell base station close to the mobile subscriber is high, and the signal strength of a cell base station far from the mobile subscriber is low. Therefore, when using IDMA to eliminate inter-cell interference, the problem of different interference signal strengths should be considered, and the conventional IDMA multi-user detection method is improved to achieve better inter-cell interference elimination effect.

Disclosure of Invention

The invention aims to overcome the defects in the prior art and provides an IDMA-based OFDM system inter-cell interference elimination method.

An OFDM system inter-cell interference elimination method based on IDMA, the OFDM system includes base transceiver station of the cell and mobile subscriber receiver, this method distinguishes different base transceiver stations of cell by disposing different interweavers; the mobile user receiver adopts IDMA multi-user detection method to eliminate the interference between cells.

In the method for eliminating interference between cells of the OFDM system based on IDMA, the signal processing step of the cell base station transmitter includes:

(2.1) the coding unit C codes and spreads the transmission data;

(2.2) the interleaver pi performs interleaving processing on the data processed by the coding unit; different cell base stations use different interleaving patterns;

(2.3) the inverse fourier transform unit IFFT performs inverse fourier transform processing on the interleaved data, generates an OFDM signal, and transmits it through an antenna.

In the method for eliminating interference between cells in the OFDM system based on IDMA, the signal processing step of the mobile subscriber receiver includes:

(3.1) a Fourier transform unit (FFT) for carrying out Fourier transform processing on the OFDM signal received by the antenna;

(3.2) the channel estimator CHE, which performs channel estimation by using the pilot frequency information of the received signal after FFT to obtain a channel coefficient;

(3.3) the basic signal estimator ESE initializing the prior probability likelihood ratio information to 0;

(3.4) the basic signal estimator ESE takes the received signal after FFT processing, the channel coefficient generated by the channel estimator and the prior probability likelihood ratio information as input, operates the detection algorithm of the ESE, carries out multi-user detection and outputs multi-channel log likelihood ratio information;

(3.5) Each deinterleaver π^-1Deinterleaving each path of log-likelihood ratio information output by the ESE, wherein each deinterleaver corresponds to an interleaver of each cell base station;

(3.6) each decoder DEC decodes the deinterleaved information of each path to generate log-likelihood ratio information; meanwhile, a decoder corresponding to the target cell base station outputs the sending data of the target cell base station;

(3.7) each interleaver pi, interleaving log-likelihood ratio information generated by each DEC; each interleaver is the same as the interleaver of each cell base station; interleaving the generated prior probability likelihood ratio information to input into a basic signal estimator;

and (3.8) repeating the steps (3.4) to (3.7) for iteration, wherein the more the iteration times, the better the interference elimination effect.

In the method for eliminating interference between cells of the OFDM system based on IDMA, the method for detecting multiple users includes: the mobile user receiver classifies all base stations except the T-BS of the target cell into a strong interference base station S-BS and a weak interference base station W-BS according to the strength of interference signals, processes the signals of the W-BS as Gaussian noise, and carries out iterative detection on the signals of the T-BS and the S-BS, thereby suppressing the interference outside the T-BS and obtaining the estimation data of the T-BS.

In the method for eliminating interference between cells of the OFDM system based on IDMA, the detection algorithm of the ESE treats the signal of the W-BS as gaussian noise, and performs iterative detection on the signals of the T-BS and the S-BS, and the detection algorithm is expressed by a mathematical formula:

$e_{\mathrm{ESE}}=\left(x_k\left(j\right)\right)$

<math><mrow><mo>=</mo><mi>log</mi><mrow><mo>(</mo><munder><munder><mi>&Sigma;</mi><mrow><msub><mi>I</mi><mi>m</mi></msub><mo>&Element;</mo><mrow><mo>(</mo><mn>0,1</mn><mo>)</mo></mrow></mrow></munder><mrow><mi>m</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><mrow><mo>(</mo><mi>exp</mi><mo>{</mo><mo>-</mo><mfrac><msup><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>-</mo><mrow><mo>(</mo><msub><mi>h</mi><mi>n</mi></msub><mo>+</mo><munder><mi>&Sigma;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><msup><mrow><mo>(</mo><mo>-</mo><mn>1</mn><mo>)</mo></mrow><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub></msup><msub><mi>h</mi><mi>n</mi></msub><mo>)</mo></mrow><mo>)</mo></mrow><mn>2</mn></msup><mrow><mn>2</mn><mi>Var</mi><mrow><mo>(</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow></mrow></mfrac><mo>}</mo><mo>&CenterDot;</mo><munder><mi>&Pi;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><msup><mrow><mo>(</mo><msub><mrow><mi>exp</mi><mo>{</mo><mi>e</mi></mrow><mi>DEC</mi></msub><mrow><mo>(</mo><msub><mi>x</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>}</mo><mo>)</mo></mrow><mrow><mo>(</mo><mn>1</mn><mo>-</mo><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub><mo>)</mo></mrow></msup><mo>)</mo></mrow><mo>)</mo></mrow></mrow></math>

<math><mrow><mo>-</mo><mi>log</mi><mrow><mo>(</mo><munder><munder><mi>&Sigma;</mi><mrow><msub><mi>I</mi><mi>m</mi></msub><mo>&Element;</mo><mrow><mo>(</mo><mn>0,1</mn><mo>)</mo></mrow></mrow></munder><mrow><mi>m</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><mrow><mo>(</mo><mi>exp</mi><mo>{</mo><mo>-</mo><mfrac><msup><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>-</mo><mrow><mo>(</mo><mo>-</mo><msub><mi>h</mi><mi>n</mi></msub><mo>+</mo><munder><mi>&Sigma;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><msup><mrow><mo>(</mo><mo>-</mo><mn>1</mn><mo>)</mo></mrow><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub></msup><msub><mi>h</mi><mi>n</mi></msub><mo>)</mo></mrow><mo>)</mo></mrow><mn>2</mn></msup><mrow><mn>2</mn><mi>Var</mi><mrow><mo>(</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow></mrow></mfrac><mo>}</mo><mo>&CenterDot;</mo><munderover><mi>&Pi;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mi>p</mi><mo>)</mo></mrow></mrow><mi>p</mi></munderover><msup><mrow><mo>(</mo><msub><mrow><mi>exp</mi><mo>{</mo><mi>e</mi></mrow><mi>DEC</mi></msub><mrow><mo>(</mo><msub><mi>x</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>}</mo><mo>)</mo></mrow><mrow><mo>(</mo><mn>1</mn><mo>-</mo><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub><mo>)</mo></mrow></msup><mo>)</mo></mrow><mo>)</mo></mrow></mrow></math>

<math><mrow><mi>Var</mi><mrow><mo>(</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>=</mo><mfrac><mn>1</mn><mi>J</mi></mfrac><munderover><mi>&Sigma;</mi><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>J</mi></munderover><msup><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>-</mo><munderover><mi>&Sigma;</mi><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>p</mi></munderover><msub><mi>h</mi><mi>k</mi></msub><mi>E</mi><mrow><mo>(</mo><msub><mi>x</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>)</mo></mrow><mn>2</mn></msup></mrow></math>

wherein,

$E\left(x_k\left(j\right)\right)=\tanh \left(\frac{e_{\mathrm{DEC}}\left(x_k\left(j\right)\right)}{2}\right)$

{e_ESE(x_k(j) k ∈ (1,... p) } denotes x about the ESE output_k(j) Log likelihood ratio information of (1), x_k(j) Data indicating the jth bit of the kth cell base station, p is the number of T-BS and S-BS, J is the number of bits of the current frame, r (J) is the received signal after FFT, { h_kK ∈ (1,... p) } is a channel coefficient generated by a channel estimator, e_DEC(x_k(j) K ∈ (1,... p) } is initialized to 0 and updated in iteration, and is prior probability log-likelihood ratio information generated by an iteration loop, and ζ is_k(j) Is the superposition of channel noise and all W-BS interference signals, with an approximate mean of 0 and a variance of Var (ζ)_k(j) Gaussian distribution) that by default employs BPSK modulation.

Compared with the prior art, the invention has the following advantages and technical effects: by adopting the IDMA multi-user detection method, better interference suppression performance can be obtained through iteration, and the more the iteration times, the better interference elimination effect is.

Drawings

FIG. 1 is a cellular network model of an OFDM system;

FIG. 2 is an IDMA-based OFDM system model;

fig. 3 is a structure of a coding unit of a cell base station transmitter.

Detailed description of the invention

The following further describes the implementation of the present invention with reference to the drawings, but the implementation of the present invention is not limited thereto.

The OFDM system inter-cell interference elimination method based on IDMA is to configure different interleavers to distinguish different cell base station transmitters; the mobile user receiver classifies all base stations except the T-BS of the target cell into a strong interference base station S-BS and a weak interference base station W-BS according to the strength of interference signals, processes the signals of the W-BS as Gaussian noise, and carries out iterative detection on the signals of the T-BS and the S-BS, thereby suppressing the interference outside the T-BS and obtaining the estimation data of the T-BS.

The OFDM system model based on IDMA is shown in fig. 2. There are two main parts: a cell base station transmitter and a mobile user receiver.

The cell site transmitter includes three important components: the device comprises a coding unit, an interleaver and an inverse Fourier transform unit. The signal processing step of the cell base station transmitter comprises the following steps:

1) a coding unit C for coding and spreading the transmission data, wherein the structural diagram of the coding unit is shown in fig. 3, and the coding unit mainly comprises an error correction code module and a spreading module;

2) the interleaver pi is used for interleaving the data processed by the coding unit, and different cell base stations are distinguished by using different interleaving patterns;

3) an inverse fourier transform unit IFFT performs inverse fourier transform processing on the interleaved data, generates an OFDM signal, and transmits the OFDM signal via an antenna.

The mobile subscriber receiver comprises six important components: fourier transform unit, channel estimator, basic signal estimator, de-interleaver and interleaver, and decoder. The signal processing steps of the mobile subscriber receiver include:

1) a Fourier transform unit FFT which performs Fourier transform processing on the OFDM signal received by the antenna;

2) a channel estimator CHE for performing channel estimation by using the pilot information of the received signal after FFT to obtain a channel coefficient;

3) a basic signal estimator ESE for initializing the prior probability likelihood ratio information to 0;

4) the basic signal estimator ESE takes the received signal after FFT processing, the channel coefficient generated by the channel estimator and the prior probability likelihood ratio information as input, operates the detection algorithm of the ESE, carries out multi-user detection and outputs multi-channel log likelihood ratio information;

5) each deinterleaver pi^-1Deinterleaving each path of log-likelihood ratio information output by the ESE, wherein each deinterleaver corresponds to an interleaver of each cell base station;

6) each decoder DEC decodes the deinterleaved information of each path to generate log-likelihood ratio information; meanwhile, a decoder corresponding to the target cell base station outputs the sending data of the target cell base station;

7) each interleaver pi interleaves log likelihood ratio information generated by each DEC. Each interleaver is the same as the interleaver of each cell base station; interleaving the generated prior probability likelihood ratio information to input into a basic signal estimator;

8) and (4) repeating the steps from 4) to 7) for iteration, wherein the more the iteration times, the better the interference elimination effect.

Considering the scenario shown in fig. 1, the mobile user can receive signals from N cell base stations (N is large), and p is the number of T-BS and S-BS. The signal processing step of the cell base station transmitter comprises the following steps:

1) the coding unit C is used for coding and spreading the transmitted data and mainly comprises an error correcting code module and a spreading module; for the kth cell base station, data sequence d_kGenerating a data sequence b by an error correcting code module_kPair of spread spectrum modules b_kSpreading by using preset spreading code, repeating data sequence by using repeated code in practical application, wherein the spreading code has s bits to generate data sequence c_k＝[c_k(1)，c_k(2)，c_k(3)，...，c_k(s)]；

2) The interleaver pi interleaves the data processed by the coding unit, and different cell base stations are distinguished by using different interleaving patterns; for the k cell base station, the data sequence c generated by the coding unit_kInput interleaver pi_kIn (3), obtain the interleaved data sequence x_k＝[x_k(1)，x_k(2)，x_k(3)，...，x_k(s)]；

3) The inverse Fourier transform unit IFFT performs inverse Fourier transform processing on the interleaved data to generate OFDM signals and transmits the OFDM signals through an antenna;

● the signal processing steps of the mobile subscriber receiver include:

1) the FFT carries out Fourier transform processing on OFDM signals received by an antenna to obtain signals r (J), wherein J belongs to 1 and 2, and J is the bit number of a current frame;

2) the channel estimator CHE performs channel estimation by using the pilot information of the received signal after FFT to obtain a channel coefficient estimation value { h }_k，k∈(1，...，p)}；

3) A basic signal estimator ESE for estimating prior probability likelihood ratio information e_DEC(x_k(j) K ∈ (1,..., p) } is initialized to 0;

4) basic signal estimator ESE, channel with signal r (J), J ∈ 1, 2Coefficient { h }_kK ∈ (1,... p) } and prior probability likelihood ratio information { e_DEC(x_k(j) K belongs to (1, p) as input, running an ESE detection algorithm, carrying out multi-user detection, and outputting multi-channel log-likelihood ratio information { e) }_ESE(x_k(j))，k∈(1，...，p)}；

5) Each deinterleaver (pi)^-1) For each path of log likelihood ratio information { e }_ESE(x_k(j) K ∈ (1,... p) } deinterleaves, and { e is output_ESE(c_k(j) K is (1,.. p) }, and each path of deinterleaver corresponds to an interleaver of each cell base station;

6) information e after deinterleaving in each way for each decoder DEC_ESE(c_k(j) K belongs to (1, 1.. p) } is input, and the coding code element posterior probability { L of each cell base station is generated by decoding_APP(b_k) K ∈ (1,..., p) }; l to target cell base station if set iteration number is finished_APP(b_k) Making decision and outputting data sequence

7) If the iteration has not been completed, each DEC generates each way of log-likelihood ratio information e_DEC(c_k(j))，k∈(1，...，p)}；

8) Each interleaver pi pair each way { e_DEC(c_k(j) K ∈ (1,.. p) } are interleaved to generate each path of prior probability likelihood ratio { e }_DEC(x_k(j) K belongs to (1,.. p) }, ESE is input to complete information updating, and the step 4 is returned to, so that one iteration is realized; the more the iteration times, the better the inter-cell interference cancellation effect.

● detection algorithm by ESE:

the received signal r (j) can be expressed as <math><mrow><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>=</mo><munderover><mi>&Sigma;</mi><mrow><mi>n</mi><mo>=</mo><mn>1</mn></mrow><mi>N</mi></munderover><msub><mi>h</mi><mi>n</mi></msub><msub><mi>x</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>+</mo><mi>n</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow></mrow></math>

Where { n (j) } is the additive white gaussian noise of the channel. The mobile user receiver classifies all base stations except the target cell base station T-BS into a strong interference base station S-BS and a weak interference base station W-BS according to the strength of interference signals, the sum of the numbers of the T-BS and the S-BS is p, and the expression of r (j) is rewritten into

<math><mrow><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>=</mo><munderover><mi>&Sigma;</mi><mrow><mi>n</mi><mo>=</mo><mn>1</mn></mrow><mi>p</mi></munderover><msub><mi>h</mi><mi>n</mi></msub><msub><mi>x</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>+</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow></mrow></math>

Wherein,

representing the superposition of all W-BS interfering signals and channel noise. In the case of BPSK modulation, ζ is determined according to the central limit theorem_k(j) Approximated as a mean of 0 and a variance of Var (ζ)_k(j) Gaussian distribution of). The received signal r (j) can be represented by a conditional Gaussian probability density function

<math><mrow><mi>P</mi><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>|</mo><msub><mi>x</mi><mn>1</mn></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>=</mo><mo>&PlusMinus;</mo><mn>1</mn><mo>,</mo><msub><mi>x</mi><mn>2</mn></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>=</mo><mo>&PlusMinus;</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><msub><mi>x</mi><mi>p</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>=</mo><mo>&PlusMinus;</mo><mn>1</mn><mo>)</mo></mrow></mrow></math>

<math><mrow><mo>=</mo><mfrac><mn>1</mn><msqrt><mn>2</mn><mi>&pi;Var</mi><mrow><mo>(</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow></msqrt></mfrac><mi>exp</mi><mo>{</mo><mo>-</mo><mfrac><msup><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>-</mo><mrow><mo>(</mo><mo>&PlusMinus;</mo><msub><mi>h</mi><mn>1</mn></msub><mo>&PlusMinus;</mo><msub><mi>h</mi><mn>2</mn></msub><mo>&PlusMinus;</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>&PlusMinus;</mo><msub><mi>h</mi><mi>p</mi></msub><mo>)</mo></mrow><mo>)</mo></mrow><mn>2</mn></msup><mrow><mn>2</mn><mi>Var</mi><mrow><mo>(</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow></mrow></mfrac><mo>}</mo><mo>-</mo><mo>-</mo><mo>-</mo><mrow><mo>(</mo><mn>1</mn><mo>)</mo></mrow></mrow></math>

Defining a kth cell base station signal x_k(j) Prior probability log likelihood ratio of

$e_{\mathrm{DEC}}\left(x_k\left(j\right)\right)=\log \left(\frac{P(x_k\left(j\right)=+1)}{P\left(x_k\left(j\right)\right)=-1}\right)---\left(2\right)$

ESE outputs log-likelihood ratio extrinsic information

$e_{\mathrm{ESE}}\left(x_k\left(j\right)\right)=\log \left(\frac{P\left(r\left(j\right)\right|x_k\left(j\right)=+1)}{P\left({r\left(j\right)|x}_k\left(j\right)\right)=-1}\right)---\left(3\right)$

Obtainable from the formula (2)

$\left\{\begin{array}{c}P(x_k\left(j\right)=+1)=\frac{e^{e_{\mathrm{DEC}}\left(x_k\left(j\right)\right)}}{e^{e_{\mathrm{DEC}}\left(x_k\left(k\right)\right)}+1}\\ P(x_k\left(j\right)=-1)=\frac{1}{e^{e_{\mathrm{DWC}}\left(x_k\left(j\right)\right)}+1}\end{array}\right.---\left(4\right)$

Based on conditional probability formula <math><mrow><mi>P</mi><mrow><mo>(</mo><mi>A</mi><mo>|</mo><mi>B</mi><mo>)</mo></mrow><mo>=</mo><munder><mi>&Sigma;</mi><mi>i</mi></munder><mi>P</mi><mrow><mo>(</mo><mi>A</mi><mo>|</mo><mi>B</mi><msub><mi>C</mi><mi>i</mi></msub><mo>)</mo></mrow><mo>*</mo><mi>P</mi><mrow><mo>(</mo><msub><mi>C</mi><mi>i</mi></msub><mo>)</mo></mrow></mrow></math>

By direct calculation, the signal processing algorithm of ESE can be obtained

$e_{\mathrm{ESE}}=\left(x_k\left(j\right)\right)$

<math><mrow><mo>=</mo><mi>log</mi><mrow><mo>(</mo><munder><munder><mi>&Sigma;</mi><mrow><msub><mi>I</mi><mi>m</mi></msub><mo>&Element;</mo><mrow><mo>(</mo><mn>0,1</mn><mo>)</mo></mrow></mrow></munder><mrow><mi>m</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><mrow><mo>(</mo><mi>exp</mi><mo>{</mo><mo>-</mo><mfrac><msup><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>-</mo><mrow><mo>(</mo><msub><mi>h</mi><mi>n</mi></msub><mo>+</mo><munder><mi>&Sigma;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><msup><mrow><mo>(</mo><mo>-</mo><mn>1</mn><mo>)</mo></mrow><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub></msup><msub><mi>h</mi><mi>n</mi></msub><mo>)</mo></mrow><mo>)</mo></mrow><mn>2</mn></msup><mrow><mn>2</mn><mi>Var</mi><mrow><mo>(</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow></mrow></mfrac><mo>}</mo><mo>&CenterDot;</mo><munder><mi>&Pi;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><msup><mrow><mo>(</mo><msub><mrow><mi>exp</mi><mo>{</mo><mi>e</mi></mrow><mi>DEC</mi></msub><mrow><mo>(</mo><msub><mi>x</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>}</mo><mo>)</mo></mrow><mrow><mo>(</mo><mn>1</mn><mo>-</mo><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub><mo>)</mo></mrow></msup><mo>)</mo></mrow><mo>)</mo></mrow></mrow></math>

<math><mrow><mo>-</mo><mi>log</mi><mrow><mo>(</mo><munder><munder><mi>&Sigma;</mi><mrow><msub><mi>I</mi><mi>m</mi></msub><mo>&Element;</mo><mrow><mo>(</mo><mn>0,1</mn><mo>)</mo></mrow></mrow></munder><mrow><mi>m</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><mrow><mo>(</mo><mi>exp</mi><mo>{</mo><mo>-</mo><mfrac><msup><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>-</mo><mrow><mo>(</mo><mo>-</mo><msub><mi>h</mi><mi>n</mi></msub><mo>+</mo><munder><mi>&Sigma;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><msup><mrow><mo>(</mo><mo>-</mo><mn>1</mn><mo>)</mo></mrow><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub></msup><msub><mi>h</mi><mi>n</mi></msub><mo>)</mo></mrow><mo>)</mo></mrow><mn>2</mn></msup><mrow><mn>2</mn><mi>Var</mi><mrow><mo>(</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow></mrow></mfrac><mo>}</mo><mo>&CenterDot;</mo><munderover><mi>&Pi;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mi>p</mi><mo>)</mo></mrow></mrow><mi>p</mi></munderover><msup><mrow><mo>(</mo><msub><mrow><mi>exp</mi><mo>{</mo><mi>e</mi></mrow><mi>DEC</mi></msub><mrow><mo>(</mo><msub><mi>x</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>}</mo><mo>)</mo></mrow><mrow><mo>(</mo><mn>1</mn><mo>-</mo><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub><mo>)</mo></mrow></msup><mo>)</mo></mrow><mo>)</mo></mrow></mrow></math>

<math><mrow><mi>Var</mi><mrow><mo>(</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>=</mo><mfrac><mn>1</mn><mi>J</mi></mfrac><munderover><mi>&Sigma;</mi><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>J</mi></munderover><msup><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>-</mo><munderover><mi>&Sigma;</mi><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>p</mi></munderover><msub><mi>h</mi><mi>k</mi></msub><mi>E</mi><mrow><mo>(</mo><msub><mi>x</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>)</mo></mrow><mn>2</mn></msup></mrow></math>

Wherein,

$E\left(x_k\left(j\right)\right)=\tanh \left(\frac{e_{\mathrm{DEC}}\left(x_k\left(j\right)\right)}{2}\right)$

● DEC Signal processing flow:

1) input e_ESE(c_k(j) To b) of_kAnd (3) carrying out soft estimation:

<math><mrow><mi>L</mi><mrow><mo>(</mo><msub><mi>b</mi><mi>k</mi></msub><mo>)</mo></mrow><mo>=</mo><munderover><mi>&Sigma;</mi><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>S</mi></munderover><msub><mi>e</mi><mi>ESE</mi></msub><mrow><mo>(</mo><msub><mi>c</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>=</mo><munderover><mi>&Sigma;</mi><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>S</mi></munderover><mi>log</mi><mrow><mo>(</mo><mfrac><mrow><mi>P</mi><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>|</mo><msub><mi>c</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>=</mo><mo>+</mo><mn>1</mn><mo>)</mo></mrow></mrow><mrow><mi>P</mi><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>|</mo><msub><mi>c</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>=</mo><mo>-</mo><mn>1</mn><mo>)</mo></mrow></mrow></mfrac><mo>)</mo></mrow></mrow></math>

where s is the number of bits of the spreading repetition code;

2) to L (b)_k) Performing posterior probability decoding of forward error correction coding to generate posterior probability L of coding code element of k cell base station_APP(b_k) I.e. by

3) Spread spectrum generation L_APP(c_k(j))＝L_APP(b_k) J 1, 2.., S, and generates log-likelihood ratio information e_DEC(c_k(j))

$e_{\mathrm{DEC}}\left(c_k\left(j\right)\right)=L_{\mathrm{APP}}\left(c_k\left(j\right)\right)-e_{\mathrm{ESE}}\left(c_k\left(j\right)\right)$

$=\log \left(\frac{P(c_k\left(j\right)=+1|r\left(j\right))}{P(c_k\left(j\right)=-1\left|r\left(j\right)\right)}\right)-e_{\mathrm{ESE}}\left(c_k\left(j\right)\right)$

$=\log \left(\frac{P(c_k\left(j\right)=+1)}{P(c_k\left(j\right)=-1)}\right)$

4) After the iteration is completed, the pair L_APP(b_k) Hard decision is made and an estimated value is output

Claims (5)

1. An OFDM system inter-cell interference elimination method based on IDMA, the OFDM system includes cell base station transmitter and mobile user receiver, its characteristic is: differentiating different cell base station transmitters by configuring different interleavers; the mobile user receiver adopts IDMA multi-user detection method to eliminate the interference between cells.

2. The IDMA-based OFDM system inter-cell interference cancellation method of claim 1, wherein the signal processing step of the cell base station transmitter comprises:

(2.1) the coding unit C codes and spreads the transmission data;

(2.2) the interleaver pi performs interleaving processing on the data processed by the coding unit; different cell base stations use different interleaving patterns;

(2.3) the inverse fourier transform unit IFFT performs inverse fourier transform processing on the interleaved data, generates an OFDM signal, and transmits it through an antenna.

3. The method of claim 1 wherein the signal processing step of the mobile subscriber receiver comprises:

(3.1) a Fourier transform unit (FFT) for carrying out Fourier transform processing on the OFDM signal received by the antenna;

(3.2) the channel estimator CHE, which performs channel estimation by using the pilot frequency information of the received signal after FFT to obtain a channel coefficient;

(3.3) the basic signal estimator ESE initializing the prior probability likelihood ratio information to 0;

(3.4) the basic signal estimator ESE takes the received signal after FFT processing, the channel coefficient generated by the channel estimator and the prior probability likelihood ratio information as input, operates the detection algorithm of the ESE, carries out multi-user detection and outputs multi-channel log likelihood ratio information;

(3.5) Each deinterleaver π^-1Deinterleaving each path of log-likelihood ratio information output by the ESE, wherein each deinterleaver corresponds to an interleaver of each cell base station;

(3.6) each decoder DEC decodes the deinterleaved information of each path to generate log-likelihood ratio information; meanwhile, a decoder corresponding to the target cell base station outputs the sending data of the target cell base station;

(3.7) each interleaver pi, interleaving log-likelihood ratio information generated by each DEC; each interleaver is the same as the interleaver of each cell base station; interleaving the generated prior probability likelihood ratio information to input into a basic signal estimator;

and (3.8) repeating the steps 4) to 7) for iteration, wherein the more the iteration times, the better the interference elimination effect.

4. The method for eliminating interference between cells in OFDM system based on IDMA as claimed in claim 1 or 3, wherein said method for multi-user detection is: the mobile user receiver classifies all base stations except the T-BS of the target cell into a strong interference base station S-BS and a weak interference base station W-BS according to the strength of interference signals, processes the signals of the W-BS as Gaussian noise, and carries out iterative detection on the signals of the T-BS and the S-BS, thereby suppressing the interference outside the T-BS and obtaining the estimation data of the T-BS.

5. The method of claim 3, wherein the detection algorithm of the ESE treats the signal of the W-BS as Gaussian noise, and performs iterative detection on the signals of the T-BS and the S-BS, and the detection algorithm is expressed by the following mathematical expression:

$e_{\mathrm{ESE}}=\left(x_k\left(j\right)\right)$

<math><mrow><mo>=</mo><mi>log</mi><mrow><mo>(</mo><munder><munder><mi>&Sigma;</mi><mrow><msub><mi>I</mi><mi>m</mi></msub><mo>&Element;</mo><mrow><mo>(</mo><mn>0,1</mn><mo>)</mo></mrow></mrow></munder><mrow><mi>m</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><mrow><mo>(</mo><mi>exp</mi><mo>{</mo><mo>-</mo><mfrac><msup><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>-</mo><mrow><mo>(</mo><msub><mi>h</mi><mi>n</mi></msub><mo>+</mo><munder><mi>&Sigma;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><msup><mrow><mo>(</mo><mo>-</mo><mn>1</mn><mo>)</mo></mrow><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub></msup><msub><mi>h</mi><mi>n</mi></msub><mo>)</mo></mrow><mo>)</mo></mrow><mn>2</mn></msup><mrow><mn>2</mn><mi>Var</mi><mrow><mo>(</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow></mrow></mfrac><mo>}</mo><mo>&CenterDot;</mo><munder><mi>&Pi;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><msup><mrow><mo>(</mo><msub><mrow><mi>exp</mi><mo>{</mo><mi>e</mi></mrow><mi>DEC</mi></msub><mrow><mo>(</mo><msub><mi>x</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>}</mo><mo>)</mo></mrow><mrow><mo>(</mo><mn>1</mn><mo>-</mo><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub><mo>)</mo></mrow></msup><mo>)</mo></mrow><mo>)</mo></mrow></mrow></math>

<math><mrow><mo>-</mo><mi>log</mi><mrow><mo>(</mo><munder><munder><mi>&Sigma;</mi><mrow><msub><mi>I</mi><mi>m</mi></msub><mo>&Element;</mo><mrow><mo>(</mo><mn>0,1</mn><mo>)</mo></mrow></mrow></munder><mrow><mi>m</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><mrow><mo>(</mo><mi>exp</mi><mo>{</mo><mo>-</mo><mfrac><msup><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>-</mo><mrow><mo>(</mo><mo>-</mo><msub><mi>h</mi><mi>n</mi></msub><mo>+</mo><munder><mi>&Sigma;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>p</mi><mo>)</mo></mrow></mrow></munder><msup><mrow><mo>(</mo><mo>-</mo><mn>1</mn><mo>)</mo></mrow><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub></msup><msub><mi>h</mi><mi>n</mi></msub><mo>)</mo></mrow><mo>)</mo></mrow><mn>2</mn></msup><mrow><mn>2</mn><mi>Var</mi><mrow><mo>(</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow></mrow></mfrac><mo>}</mo><mo>&CenterDot;</mo><munderover><mi>&Pi;</mi><mrow><mi>n</mi><mo>&NotEqual;</mo><mi>k</mi><mo>,</mo><mi>n</mi><mo>&Element;</mo><mrow><mo>(</mo><mn>1</mn><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mi>p</mi><mo>)</mo></mrow></mrow><mi>p</mi></munderover><msup><mrow><mo>(</mo><msub><mrow><mi>exp</mi><mo>{</mo><mi>e</mi></mrow><mi>DEC</mi></msub><mrow><mo>(</mo><msub><mi>x</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>}</mo><mo>)</mo></mrow><mrow><mo>(</mo><mn>1</mn><mo>-</mo><msub><mi>I</mi><mrow><mi>n</mi><mo>-</mo><mn>1</mn></mrow></msub><mo>)</mo></mrow></msup><mo>)</mo></mrow><mo>)</mo></mrow></mrow></math>

<math><mrow><mi>Var</mi><mrow><mo>(</mo><msub><mi>&zeta;</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>=</mo><mfrac><mn>1</mn><mi>J</mi></mfrac><munderover><mi>&Sigma;</mi><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>J</mi></munderover><msup><mrow><mo>(</mo><mi>r</mi><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>-</mo><munderover><mi>&Sigma;</mi><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>p</mi></munderover><msub><mi>h</mi><mi>k</mi></msub><mi>E</mi><mrow><mo>(</mo><msub><mi>x</mi><mi>k</mi></msub><mrow><mo>(</mo><mi>j</mi><mo>)</mo></mrow><mo>)</mo></mrow><mo>)</mo></mrow><mn>2</mn></msup></mrow></math>

wherein,

$E\left(x_k\left(j\right)\right)=\tanh \left(\frac{e_{\mathrm{DEC}}\left(x_k\left(j\right)\right)}{2}\right)$

wherein, { e_ESE(x_k(j) K ∈ (1,... p) } denotes x about the ESE output_k(j) Log likelihood ratio information of (1), x_k(j) Data indicating the jth bit of the kth cell base station, p is the number of T-BS and S-BS, J is the number of bits of the current frame, r (J) is the received signal after FFT, { h_kK ∈ (1,... p) } is a channel coefficient generated by a channel estimator, e_DEC(x_k(j) K ∈ (1,... p) } is initialized to 0 and updated in iteration, and is prior probability log-likelihood ratio information generated by an iteration loop, and ζ is_k(j) Is the superposition of channel noise and all W-BS interference signals, with an approximate mean of 0 and a variance of Var (ζ)_k(j) Gaussian distribution) that by default employs BPSK modulation.

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