Background
To meet the increasing rate demands of users, existing CDMA wireless communication systems introduce various technologies with higher and higher peak rates, such as HSDPA (high speed downlink packet access) and HSUPA (high speed uplink packet access). The introduction of these new techniques presents significant challenges to conventional RAKE reception techniques.
The RAKE receiver is the best receiver under white gaussian noise, and when the spreading factor is large, the interference in the channel can be considered to be approximately whitened, so that the optimal performance can be approximately obtained; however, when the spreading factor is small, the interference between multipath and the interference between multiple users are increased, and the colored component in the noise is increased, so that the RAKE receiver is difficult to fully compensate the interference in the channel, and the application of high-speed packet service is limited.
The GRAKE receiver can change colored noise of a receiving end into white noise without changing the structure of the RAKE receiver, effectively improve the influence caused by interference among multiple paths and other users, and provide guarantee for the application of high-speed packet service in a CDMA practical system.
A typical downlink DS-CDMA system architecture is shown in fig. 1: assuming that there are K users in the system, the own user (X0) and K-1 interfering users, the ith symbol of user K is spread with spreading waveform ak,i(t) spreading, denoted sk(i) Then, the transmission signal expression of user K is as follows:
<math>
<mrow>
<msub>
<mi>x</mi>
<mi>k</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msqrt>
<msub>
<mi>E</mi>
<mi>k</mi>
</msub>
</msqrt>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mo>∞</mo>
</munderover>
<msub>
<mi>s</mi>
<mi>k</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>a</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>iT</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
wherein E iskIs the average energy of the symbol, T is the symbol period, and each data symbol energy is normalized, i.e.: | sk(i)|2=1。
Spreading waveform a of ith symbol of Kth userk,i(t) from a spreading sequence ck,i(j)}i=0 Q-1Convolved with the chip waveform p (t), as follows:
<math>
<mrow>
<msub>
<mi>a</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msqrt>
<mi>Q</mi>
</msqrt>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>c</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>j</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
wherein: q is a spreading factor, TcIs the chip period. In DS-CDMA systems, the spreading codes are mutually orthogonal, i.e.
<math>
<mrow>
<msubsup>
<mi>C</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mi>H</mi>
</msubsup>
<msub>
<mi>C</mi>
<mrow>
<mi>j</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mo>=</mo>
<mn>0</mn>
<mo>,</mo>
<mi>k</mi>
<mo>≠</mo>
<mi>j</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
Wherein C isk,i=[cki(0),cki(1),......,cki(Q-1)]TUpper label ofTDenotes transpose, and H denotes conjugate transpose.
At a sending end of a base station, signals of all K users are superposed together and then transmitted through a multipath propagation channel; the multipath channel model can be simply expressed in terms of impulse response as follows:
<math>
<mrow>
<mi>g</mi>
<mrow>
<mo>(</mo>
<mi>τ</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<mi>δ</mi>
<mrow>
<mo>(</mo>
<mi>τ</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>l</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>4</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
where L is the number of resolvable multipaths, glAnd τlRespectively the amplitude of the first path and the delay of the path.
As can be seen from equations (1) and (4), the signal at the receiving end can be expressed as follows:
<math>
<mrow>
<mi>r</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<msub>
<mi>x</mi>
<mn>0</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>l</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>+</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mrow>
<mi>K</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<msub>
<mi>x</mi>
<mi>k</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>l</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mi>n</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>5</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
where n (t) is interference, including inter-cell interference and thermal noise.
At a receiving end, a received signal firstly passes through a pulse shaping filter which is the same as that of the transmitting end, then is despread, and finally a target signal is obtained through weighting and combining. The above process is implemented by a GRAKE receiver, the GRAKE structure is shown in fig. 2.
The operation of the GRAKE receiver will be described with respect to the detection of the first symbol of the first user. The detection of the symbol can be expressed by the following formula:
<math>
<mrow>
<mi>y</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>d</mi>
<mi>j</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msubsup>
<mo>∫</mo>
<mrow>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mrow>
<mo>+</mo>
<mo>∞</mo>
</mrow>
</msubsup>
<mi>r</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>+</mo>
<msub>
<mi>d</mi>
<mi>j</mi>
</msub>
<mo>)</mo>
</mrow>
<msubsup>
<mi>a</mi>
<mn>0,0</mn>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mi>dt</mi>
<mo>;</mo>
<mi>j</mi>
<mo>=</mo>
<mn>1,2</mn>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
<mi>J</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>6</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
the de-spreading sequence is formed by combining the weight w ═ w1,w2,...,wj]TProduces a decision statistic variable z:
<math>
<mrow>
<mi>z</mi>
<mo>=</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>J</mi>
</munderover>
<msubsup>
<mi>w</mi>
<mi>j</mi>
<mo>*</mo>
</msubsup>
<mi>y</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>d</mi>
<mi>j</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msup>
<mi>w</mi>
<mi>H</mi>
</msup>
<mi>y</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>7</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
wherein y ═ y (d)1),y(d2),...,y(dJ)]T
In the receiver, the number and delay of fingers are equal to the number and delay of paths of the channel, respectively, i.e.: j ═ L, dj=τj1, j 1,2, the L weighting factor is the amplitude w of the channel pathj=gj-1,j=1,2,...,L。
The existing GRAKE receiver and RAKE receiver have the same parameters, i.e. the number J of fingers, and the delay { d of fingers { D }j}j=1 JAnd a combining weight { wj}j=1 J(ii) a The difference is that the GRAKE has different combining weight determination methods and the GRAKE receiver has a significant performance improvement because it has a finger number exceeding the channel detectable path.
And (3) determining the combining weight and finger delay:
assuming we are only interested in the first symbol of the first user (others can be analogized), the despread signal can be expressed as follows:
y=hs0(0)+u (8)
s0(0) which is the symbol we are interested in, h is the quantity related to the fading information of each path, called the fading function of each path. u is the sum of all noise and interference, with a mean of 0 and a variance of Ru=E[uuH]The combined weight is:
the despread signal can be derived from equation 5 as:
<math>
<mrow>
<mi>y</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msubsup>
<mo>∫</mo>
<mrow>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mo>∞</mo>
</msubsup>
<mi>r</mi>
<mrow>
<mo>(</mo>
<mi>τ</mi>
<mo>)</mo>
</mrow>
<msubsup>
<mi>a</mi>
<mn>0,0</mn>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<mi>τ</mi>
<mo>-</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mi>dτ</mi>
</mrow>
</math>
<math>
<mrow>
<mo>=</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>κ</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>K</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mo>∞</mo>
</munderover>
<msqrt>
<msub>
<mi>E</mi>
<mi>k</mi>
</msub>
</msqrt>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<msub>
<mi>s</mi>
<mi>k</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>R</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>iT</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>l</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mover>
<mi>n</mi>
<mo>~</mo>
</mover>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>10</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
wherein:is noise after pulse shaping, Rk,i(t) is the cross-correlation function of the other symbols and the first symbol of the first code channel.
<math>
<mrow>
<msub>
<mi>R</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msubsup>
<mo>∫</mo>
<mrow>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mo>∞</mo>
</msubsup>
<msub>
<mi>a</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>+</mo>
<mi>τ</mi>
<mo>)</mo>
</mrow>
<msubsup>
<mi>a</mi>
<mn>0,0</mn>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<mi>τ</mi>
<mo>)</mo>
</mrow>
<mi>dτ</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>11</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
Will be given in equation 2 <math>
<mrow>
<msub>
<mi>a</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msqrt>
<mi>Q</mi>
</msqrt>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>c</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>j</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</math> Substituting equation 11 yields:
<math>
<mrow>
<msub>
<mi>R</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mi>Q</mi>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>c</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>)</mo>
</mrow>
<msubsup>
<mi>c</mi>
<mn>0,0</mn>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>R</mi>
<mi>p</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>-</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>12</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
wherein: <math>
<mrow>
<msub>
<mi>R</mi>
<mi>p</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msubsup>
<mo>∫</mo>
<mrow>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mo>∞</mo>
</msubsup>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>+</mo>
<mi>τ</mi>
<mo>)</mo>
</mrow>
<msup>
<mi>p</mi>
<mo>*</mo>
</msup>
<mrow>
<mo>(</mo>
<mi>τ</mi>
<mo>)</mo>
</mrow>
<mi>dτ</mi>
</mrow>
</math> is the autocorrelation function of the chip waveform.
Ck,i(m) may be represented as follows:
<math>
<mrow>
<msub>
<mi>C</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfenced open='{' close=''>
<mtable>
<mtr>
<mtd>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
<mo>-</mo>
<mi>m</mi>
</mrow>
</munderover>
<msub>
<mi>c</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
<msubsup>
<mi>c</mi>
<mn>0,0</mn>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>+</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<mo>,</mo>
</mtd>
<mtd>
<mn>0</mn>
<mo>≤</mo>
<mi>m</mi>
<mo>≤</mo>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mtd>
</mtr>
<mtr>
<mtd>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
<mo>+</mo>
<mi>m</mi>
</mrow>
</munderover>
<msub>
<mi>c</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>-</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<msubsup>
<mi>c</mi>
<mn>0,0</mn>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
<mo>,</mo>
</mtd>
<mtd>
<mn>1</mn>
<mo>-</mo>
<mi>Q</mi>
<mo>≤</mo>
<mi>m</mi>
<mo><</mo>
<mn>0</mn>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>13</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
from equation 13, equation 12 can be abbreviated as:
<math>
<mrow>
<msub>
<mi>R</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mi>Q</mi>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
<mo>-</mo>
<mi>Q</mi>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>C</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>R</mi>
<mi>p</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>+</mo>
<mi>m</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>14</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
since the spreading codes are orthogonal to each other, we can obtain: ck,0(0)=0,k≠0;C0,0(0) Q. Thermal noise after pulse shapingThe autocorrelation function of (a) is:
<math>
<mrow>
<mo>=</mo>
<mfrac>
<msub>
<mi>N</mi>
<mn>0</mn>
</msub>
<mi>Q</mi>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
<mo>-</mo>
<mi>Q</mi>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>C</mi>
<mn>0,0</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>R</mi>
<mi>p</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>-</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>+</mo>
<mi>m</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</math>
according to equation 10, the despread signal can be divided into the following four parts by composition: user desired part yd(t), self-interference part yISI(t) multiple access interference yMUI(t) and thermal noise n' (t). Namely:
<math>
<mrow>
<mi>y</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msqrt>
<msub>
<mi>E</mi>
<mn>0</mn>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>d</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>s</mi>
<mn>0</mn>
</msub>
<mrow>
<mo>(</mo>
<mn>0</mn>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msqrt>
<msub>
<mi>E</mi>
<mn>0</mn>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>ISI</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msqrt>
<msub>
<mi>E</mi>
<mi>I</mi>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>MUI</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msqrt>
<msub>
<mi>N</mi>
<mn>0</mn>
</msub>
</msqrt>
<msup>
<mi>n</mi>
<mo>′</mo>
</msup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>16</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
wherein:
<math>
<mrow>
<msub>
<mi>y</mi>
<mi>d</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<msub>
<mi>R</mi>
<mn>0,0</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>l</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>17</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
<math>
<mrow>
<msub>
<mi>y</mi>
<mi>ISI</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mi>Σ</mi>
<munder>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mrow>
<mi>i</mi>
<mo>≠</mo>
<mn>0</mn>
</mrow>
</munder>
<mo>∞</mo>
</munderover>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<msub>
<mi>s</mi>
<mn>0</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>R</mi>
<mrow>
<mn>0</mn>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>iT</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>l</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>18</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
<math>
<mrow>
<msub>
<mi>y</mi>
<mi>MUI</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msqrt>
<msub>
<mi>E</mi>
<mi>I</mi>
</msub>
</msqrt>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mrow>
<mi>K</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msqrt>
<msub>
<mi>E</mi>
<mi>k</mi>
</msub>
</msqrt>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mo>∞</mo>
</munderover>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<msub>
<mi>s</mi>
<mi>k</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>R</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>iT</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>l</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>19</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
wherein, <math>
<mrow>
<msub>
<mi>E</mi>
<mi>I</mi>
</msub>
<mo>=</mo>
<msubsup>
<mi>Σ</mi>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mrow>
<mi>K</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msubsup>
<msub>
<mi>E</mi>
<mi>k</mi>
</msub>
</mrow>
</math> is the symbol energy, N, of all interference within a cell0Is gaussian white noise power.
At each delay time (d) of the diameter1,d2,...,dJ) Sampling the output of the matched filter to obtain y ═ y (d)1),y(d2),...,y(dJ)]T。
The specific expression of y is obtained from equation 16:
<math>
<mrow>
<mi>y</mi>
<mo>=</mo>
<msqrt>
<msub>
<mi>E</mi>
<mn>0</mn>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>d</mi>
</msub>
<msub>
<mi>s</mi>
<mn>0</mn>
</msub>
<mrow>
<mo>(</mo>
<mn>0</mn>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msqrt>
<msub>
<mi>E</mi>
<mn>0</mn>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>ISI</mi>
</msub>
<mo>+</mo>
<msqrt>
<msub>
<mi>E</mi>
<mi>I</mi>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>MUI</mi>
</msub>
<mo>+</mo>
<msqrt>
<msub>
<mi>N</mi>
<mn>0</mn>
</msub>
</msqrt>
<msup>
<mi>n</mi>
<mo>′</mo>
</msup>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>20</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
wherein: y ═ y (d)1),y(d2),...,y(dJ)]T,
yISI=[yISI(d1),yISI(d2),...,yISI(dJ)]T,
yMUI=[yMUI(d1),yMUI(d2),...,yMUI(dJ)]T
n′=[n′(d1),n′(d2),...,n′(dJ)]T,
<math>
<mrow>
<mi>u</mi>
<mo>=</mo>
<msqrt>
<msub>
<mi>E</mi>
<mn>0</mn>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>ISI</mi>
</msub>
<mo>+</mo>
<msqrt>
<msub>
<mi>E</mi>
<mi>I</mi>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>MUI</mi>
</msub>
<mo>+</mo>
<msqrt>
<msub>
<mi>N</mi>
<mn>0</mn>
</msub>
</msqrt>
<msup>
<mi>n</mi>
<mo>′</mo>
</msup>
</mrow>
</math> Is the sum of all interference and noise.
Suppose yISI(t),yMUI(t) and n' (t) are independent, then:
Ru=E0RISI+EIRMUI+N0Rn′ (21)
wherein: Rn′=E[n′n′H]。
since the spreading codes are orthogonal to each other and according to equation (13) Ck,i(m) deriving the following two formulae:
<math>
<mrow>
<mi>E</mi>
<mo>[</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<msubsup>
<mi>C</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
<mo>]</mo>
<mo>=</mo>
<mn>0</mn>
<mo>,</mo>
<mi>m</mi>
<mo>≠</mo>
<mi>n</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>22</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
according to the formulas 20, 22 and 23, R in the matrix can be calculatedISI,RMUI,Rn′The respective elements of (a) are as follows:
<math>
<mrow>
<mo>=</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>q</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mi>Σ</mi>
<munder>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mrow>
<mi>i</mi>
<mo>≠</mo>
</mrow>
</munder>
<mo>∞</mo>
</munderover>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<msubsup>
<mi>g</mi>
<mi>q</mi>
<mo>*</mo>
</msubsup>
<mi>E</mi>
<mo>[</mo>
<msub>
<mi>R</mi>
<mrow>
<mn>0</mn>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>d</mi>
<mn>1</mn>
</msub>
<mo>-</mo>
<mi>iT</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>l</mi>
</msub>
<mo>)</mo>
</mrow>
<msubsup>
<mi>R</mi>
<mrow>
<mn>0</mn>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<msub>
<mi>d</mi>
<mn>2</mn>
</msub>
<mo>-</mo>
<mi>iT</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>q</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>]</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>24</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
<math>
<mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msup>
<mi>Q</mi>
<mn>2</mn>
</msup>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>q</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mi>Σ</mi>
<munder>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mrow>
<mi>i</mi>
<mo>≠</mo>
<mn>0</mn>
</mrow>
</munder>
<mo>∞</mo>
</munderover>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<msubsup>
<mi>g</mi>
<mi>q</mi>
<mo>*</mo>
</msubsup>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
<mo>-</mo>
<mi>Q</mi>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mrow>
<mo>(</mo>
<mi>Q</mi>
<mo>-</mo>
<mo>|</mo>
<mi>m</mi>
<mo>|</mo>
<mo>)</mo>
</mrow>
<msub>
<mi>R</mi>
<mi>p</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>d</mi>
<mn>1</mn>
</msub>
<mo>-</mo>
<mi>m</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>-</mo>
<mi>iT</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>l</mi>
</msub>
<mo>)</mo>
</mrow>
<msubsup>
<mi>R</mi>
<mi>p</mi>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<msub>
<mi>d</mi>
<mn>2</mn>
</msub>
<mo>-</mo>
<mi>m</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>-</mo>
<mi>iT</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>q</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</math>
<math>
<mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msup>
<mi>Q</mi>
<mn>2</mn>
</msup>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>q</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<msubsup>
<mi>g</mi>
<mi>q</mi>
<mo>*</mo>
</msubsup>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mo>∞</mo>
</munderover>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<msubsup>
<mi>g</mi>
<mi>q</mi>
<mo>*</mo>
</msubsup>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
<mo>-</mo>
<mi>Q</mi>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mrow>
<mo>(</mo>
<mi>Q</mi>
<mo>-</mo>
<mo>|</mo>
<mi>m</mi>
<mo>|</mo>
<mo>)</mo>
</mrow>
<msub>
<mi>R</mi>
<mi>p</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>d</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<mi>m</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>-</mo>
<mi>iT</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>l</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>25</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
<math>
<mrow>
<mo>×</mo>
<msubsup>
<mi>R</mi>
<mi>p</mi>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<msub>
<mi>d</mi>
<mn>2</mn>
</msub>
<mo>+</mo>
<mi>m</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>-</mo>
<mi>iT</mi>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>q</mi>
</msub>
<mo>)</mo>
</mrow>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>-</mo>
<mi>δ</mi>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<mi>δ</mi>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<mo>)</mo>
</mrow>
</mrow>
</math>
<math>
<mrow>
<msub>
<mi>R</mi>
<msup>
<mi>n</mi>
<mo>′</mo>
</msup>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>d</mi>
<mn>1</mn>
</msub>
<mo>,</mo>
<msub>
<mi>d</mi>
<mn>2</mn>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>E</mi>
<mo>[</mo>
<msup>
<mi>n</mi>
<mo>′</mo>
</msup>
<mrow>
<mo>(</mo>
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<mi>d</mi>
<mn>1</mn>
</msub>
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<msup>
<mrow>
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<mi>n</mi>
<mo>′</mo>
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<msub>
<mi>d</mi>
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<mo>)</mo>
</mrow>
<mo>*</mo>
</msup>
<mo>]</mo>
</mrow>
</math>
<math>
<mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mi>Q</mi>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
<mo>-</mo>
<mi>Q</mi>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>C</mi>
<mn>0,0</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
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</mrow>
<msub>
<mi>R</mi>
<mi>p</mi>
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<mrow>
<mo>(</mo>
<msub>
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<mn>1</mn>
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<mo>-</mo>
<msub>
<mi>d</mi>
<mn>2</mn>
</msub>
<mo>+</mo>
<mi>m</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</math>
<math>
<mrow>
<msub>
<mi>y</mi>
<mi>d</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>d</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mi>Q</mi>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>l</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>L</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>g</mi>
<mi>l</mi>
</msub>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
<mo>-</mo>
<mi>Q</mi>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msub>
<mi>C</mi>
<mn>0,0</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>R</mi>
<mi>p</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>d</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<mi>m</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>-</mo>
<msub>
<mi>τ</mi>
<mi>l</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>27</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
it can be seen from the above derivation formula that the combining weight determination method adopted by the existing GRAKE receiver needs to calculate RISIAnd RMUITherefore, the operation overhead is very high, the implementation complexity is high, and the hardware implementation is not facilitated.
Disclosure of Invention
To solve the above problems, the present invention provides a combining weight calculation method for a GRAKE receiver, wherein R isuCalculating the total interference y by using an angular symmetry matrixiAnd (t) obtaining the autocorrelation function, and greatly reducing the operation complexity of the GRAKE receiver by adopting the method.
A combining weight calculation method of a GRAKE receiver comprises the following steps:
step A: obtaining a function of the demodulated interference portion:
b, selecting a finger position;
and C: constructing an angle symmetric matrix;
step D: computing R using an angularly symmetric matrixu;
Step E: according to Calculating a combined weight;
wherein R isuH is the impulse response estimated from the channel as the autocorrelation function of the total interference.
The finger position selection method can be as follows: determining the number J of fingers, namely taking the value of J in the interval of [ L,2L-1 ]; selecting J finger positions according to the positions of the L paths estimated by the channel, namely the rear L positions of the fingers are the same as the positions of the paths estimated by the channel, and the front J-L finger positions and the J-L paths in front of the L paths are symmetrical about the strongest path;
wherein, L is the number of paths estimated by the channel.
The angle symmetric matrix is a square matrix of dimension 2Q-1, a point with m being 0 is taken as a central symmetric point, and values on a main diagonal are 1,2 … Q-1,0, Q-1, …,2 and 1 in sequence;
wherein Q represents the length of the spreading code, and m is the finger position;
the R isuCan be expressed as:
<math>
<mrow>
<msub>
<mi>R</mi>
<mi>u</mi>
</msub>
<mo>=</mo>
<msub>
<mfenced open='[' close=']'>
<mtable>
<mtr>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>,</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>R</mi>
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<mi>y</mi>
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</msub>
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</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>,</mo>
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<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
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<mi>y</mi>
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</msub>
<msub>
<mi>y</mi>
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</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>,</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
</mtr>
<mtr>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
</mtr>
<mtr>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>,</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mrow>
<mi>J</mi>
<mo>×</mo>
<mi>J</mi>
</mrow>
</msub>
</mrow>
</math>
wherein,is RuThe middle element, i represents a row, j represents a column, which can be further represented as:
<math>
<mrow>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mi>L</mi>
<mo>-</mo>
<mi>i</mi>
</mrow>
<mrow>
<mi>J</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mi>g</mi>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mi>L</mi>
<mo>-</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mo>)</mo>
</mrow>
<mo>*</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mi>L</mi>
<mo>-</mo>
<mi>j</mi>
</mrow>
<mrow>
<mi>J</mi>
<mo>-</mo>
<mi>j</mi>
</mrow>
</munderover>
<mi>conj</mi>
<mrow>
<mo>(</mo>
<mi>g</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>+</mo>
<mn>1</mn>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mi>L</mi>
<mo>-</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mo>)</mo>
</mrow>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mi>MULT</mi>
<mo>_</mo>
<mi>C</mi>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>+</mo>
<mi>Q</mi>
<mo>,</mo>
<mi>n</mi>
<mo>+</mo>
<mi>Q</mi>
<mo>)</mo>
</mrow>
</mrow>
</math>
wherein MULT _ C is the angular symmetry matrix constructed in step C, SiIs an interference symbol, conj () represents a complex conjugate operation, gtIs the estimated multipath.
A GRAKE receiver comprises a combining weight calculation module and a multipath position selection module;
the combination weight calculation module adopts the combination weight calculation method to calculate the combination weight;
the multi-path position selection module is used for selecting finger positions, and the selection method comprises the following steps: determining the number J of fingers, namely taking the value of J in the interval of [ L,2L-1 ]; selecting J finger positions according to the positions of the L paths estimated by the channel, namely the rear L positions of the fingers are the same as the positions of the paths estimated by the channel, and the front J-L finger positions and the J-L paths in front of the L paths are symmetrical about the strongest path;
wherein, L is the number of radial strips estimated by the channel.
The rest of the modules can adopt the corresponding modules of the existing GRAKE receiver
The GRAKE receiver of the present invention does not need to recalculate RISIAnd RMUIBy passingThe angle symmetric matrix realizes the calculation of the combined weight, effectively reduces the calculation amount of the calculated combined weight, and improves the performance of the GRAKE receiver through the selection module of the finger position. The GRAKE receiver not only greatly reduces the calculation cost and the realization complexity, but also effectively improves the system performance.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings.
According to equations 20 and 21, the despread signal is divided into four parts: user desired part yd(t), self-interference part yISI(t) multiple access interference yMUI(t) and thermal noise n' (t):
<math>
<mrow>
<mi>y</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msqrt>
<msub>
<mi>E</mi>
<mn>0</mn>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>d</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<msub>
<mi>s</mi>
<mn>0</mn>
</msub>
<mrow>
<mo>(</mo>
<mn>0</mn>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msqrt>
<msub>
<mi>E</mi>
<mn>0</mn>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>ISI</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msqrt>
<msub>
<mi>E</mi>
<mi>I</mi>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>MUI</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msqrt>
<msub>
<mi>N</mi>
<mn>0</mn>
</msub>
</msqrt>
<msup>
<mi>n</mi>
<mo>′</mo>
</msup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
</mrow>
</math>
then the total interference is <math>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msqrt>
<msub>
<mi>E</mi>
<mn>0</mn>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>ISI</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msqrt>
<msub>
<mi>E</mi>
<mi>I</mi>
</msub>
</msqrt>
<msub>
<mi>y</mi>
<mi>MUI</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msqrt>
<msub>
<mi>N</mi>
<mn>0</mn>
</msub>
</msqrt>
<msup>
<mi>n</mi>
<mo>′</mo>
</msup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
</mrow>
</math>
And because of Ru=E0RISI+EIRMUI+N0Rn′Wherein
Rn′=E[n′n′H]
It can be seen that RuIs the total interference yi(t) autocorrelation function, then find y directlyi(t) obtaining R as an autocorrelation functionu. According to the formula Combining weights for GRAKE receivers may be obtained.
A method for calculating the combining weight of a GRAKE receiver comprises the following specific steps:
step A, obtaining a function of the demodulated interference part according to a formula 10:
assume that the receiving end receives a signal of <math>
<mrow>
<mi>r</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mi>L</mi>
</munderover>
<msub>
<mi>g</mi>
<mi>m</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>S</mi>
<mi>s</mi>
</msub>
<msub>
<mi>a</mi>
<mi>s</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>m</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msub>
<mi>S</mi>
<mi>i</mi>
</msub>
<msub>
<mi>a</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>m</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>)</mo>
</mrow>
</mrow>
</math>
Wherein SsFor the user data, SiFor interfering user data, L is the number of channel estimation paths.
By despreading, the following are obtained: <math>
<mrow>
<mi>y</mi>
<mrow>
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<mi>m</mi>
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<mi>T</mi>
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<msubsup>
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<mrow>
<mo>(</mo>
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</mrow>
<mi>r</mi>
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<mo>)</mo>
</mrow>
<mi>dt</mi>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msqrt>
<mi>Q</mi>
</msqrt>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>Q</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<msubsup>
<mi>c</mi>
<mi>s</mi>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mover>
<mi>r</mi>
<mo>~</mo>
</mover>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>+</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mrow>
</math>
wherein: c. Cs(j) Is the spreading sequence of the target signal and,is a discrete signal sequence after the received data is filtered, <math>
<mrow>
<mover>
<mi>r</mi>
<mo>~</mo>
</mover>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msubsup>
<mo>∫</mo>
<mrow>
<mo>-</mo>
<mo>∞</mo>
</mrow>
<mo>∞</mo>
</msubsup>
<mi>r</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<msup>
<mi>p</mi>
<mo>*</mo>
</msup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>j</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mi>dt</mi>
<mo>,</mo>
</mrow>
</math> the function that yields the despread interference part is: (the cross-correlation between the spreading code and the spreading code yields C, and the cross-correlation between C and C yields a matrix)
<math>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<msub>
<mi>T</mi>
<mi>c</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>t</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mi>W</mi>
</munderover>
<msub>
<mi>g</mi>
<mi>t</mi>
</msub>
<msub>
<mi>S</mi>
<mi>i</mi>
</msub>
<msub>
<mi>C</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
<mo>,</mo>
</mrow>
</math> Wherein SiIs an interference symbol, Ci(m) is the cross-correlation function between spreading codes. gtIs the estimated multipath, W is the window length of the estimated channel, typically window length ≦ spreading code length, and m is finger position.
B, selecting a finger position, namely determining an m value;
preferably, the finger position selection method comprises the following steps: determining the number J of fingers, namely taking the value of J in the interval of [ L,2L-1 ]; and selecting J finger positions according to the positions of the L paths estimated by the channel, namely the rear L positions of the fingers are the same as the positions of the paths estimated by the channel, and the front J-L finger positions and the J-L paths in front of the L paths are symmetrical about the strongest path. Wherein, L is the number of radial strips estimated by the channel.
Preferably, the process of selecting the finger location is: assuming that the number L of paths estimated by the channel is 3, and the chip positions are 0, 2, and 4, respectively, then the path can be represented as h (0), h (2), and h (4), where h (0) is the strongest path, n in h (n) represents the chip position, and h (n) represents the impulse response strength; the number J of fingers is selected to be J ═ 2 × L-1 ═ 5, and according to the method described above, the finger position is obtained to be m ═ 4, -2, 0, 2, 4.
Step C, constructing an angle symmetric matrix
It can be seen from the formula in step a that the autocorrelation function of the interference symbol is mainly calculated by calculating the correlation between the correlations of the spreading codes. Further, it can be obtained from formulas 22 and 23 that the correlation is an angle symmetric matrix symmetric to 0 point, according to the system characteristics, the window length W ═ spreading code length Q, m is the maximum value of spreading code length, the angle symmetric matrix is a square matrix MULT _ C of dimension 2Q-1, the point with m ═ 0 is the central symmetric point, and the values on the main diagonal are 1,2 … Q-1,0, Q-1, …,2,1 in sequence; in this embodiment, taking the spreading code length Q of the TD-SCDMA system as an example, the constructed angular symmetric matrix MULT _ C is represented as:
d, calculating R by utilizing the angular symmetry matrixu
RuCan be expressed as:
<math>
<mrow>
<msub>
<mi>R</mi>
<mi>u</mi>
</msub>
<mo>=</mo>
<msub>
<mfenced open='[' close=']'>
<mtable>
<mtr>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>,</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>,</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
</mtr>
<mtr>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
</mtr>
<mtr>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
<mtd>
<mo>.</mo>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mtd>
<mtd>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
</mtd>
<mtd>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>,</mo>
<mi>m</mi>
<mo>)</mo>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mrow>
<mi>J</mi>
<mo>×</mo>
<mi>J</mi>
</mrow>
</msub>
</mrow>
</math>
wherein,is RuThe middle element, i represents a row, j represents a column, which can be further represented as:
<math>
<mrow>
<msub>
<mi>R</mi>
<mrow>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mi>L</mi>
<mo>-</mo>
<mi>i</mi>
</mrow>
<mrow>
<mi>J</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mi>g</mi>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>+</mo>
<mn>1</mn>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mi>L</mi>
<mo>-</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mo>)</mo>
</mrow>
<mo>*</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mi>L</mi>
<mo>-</mo>
<mi>j</mi>
</mrow>
<mrow>
<mi>J</mi>
<mo>-</mo>
<mi>j</mi>
</mrow>
</munderover>
<mi>conj</mi>
<mrow>
<mo>(</mo>
<mi>g</mi>
<mrow>
<mo>(</mo>
<mi>n</mi>
<mo>+</mo>
<mn>1</mn>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mi>L</mi>
<mo>-</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
<mo>)</mo>
</mrow>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mi>MULT</mi>
<mo>_</mo>
<mi>C</mi>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>+</mo>
<mi>Q</mi>
<mo>,</mo>
<mi>n</mi>
<mo>+</mo>
<mi>Q</mi>
<mo>)</mo>
</mrow>
</mrow>
</math>
where L is the path of channel estimation, J is the number of fingers, J equals 2L-1 in this embodiment, and MULT _ C is the angular symmetric matrix constructed in step C.
Step E, according to Wherein h is the path estimated by the channel, and the number of the paths is L.
From the above implementation steps, it can be seen that the method greatly simplifies the implementation of GRAKE, and if the spreading codes are large, the correlation matrix of the correlations of all the spreading codes does not need to be stored, only the matrix of the number of the estimation paths needs to be stored, and the matrix is read according to the symmetry.
A GRAKE receiver comprises a combining weight calculation module and a multipath position selection module;
the combination weight calculation module adopts the combination weight calculation method to calculate the combination weight;
the multi-path position selection module is used for selecting finger positions, and the selection method comprises the following steps: determining the number J of fingers, namely taking the value of J in the interval of [ L,2L-1 ]; and selecting J finger positions according to the positions of the L paths estimated by the channel, namely the rear L positions of the fingers are the same as the positions of the paths estimated by the channel, and the front J-L finger positions and the J-L paths in front of the L paths are symmetrical about the strongest path. Wherein, L is the number of radial strips estimated by the channel.
The purpose, technical solutions and advantages of the present invention are further described in detail by the examples given in the present invention, and it should be understood that the examples given above are only preferred embodiments of the present invention, and are not intended to limit the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.