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Deviation is defined as the ratio of the nonlinearity producing term to the desired term. Hence computing the minimum
deviation with respect to bias current yields
ev;
[.[OZV:.
112
+ 2@ + OZyW2)b”+ (1 + 2@@”2 +
02y2@),]
(4)
Computing an average for I,,, over the entire input range
yields a value of 16.1 pA for e = 560 pV and the other parameters as previously defined. This value is again close to the
experimentally determined value of 17 pA.
-
Conclusion: A simple linear CMOS circuit to compute a ‘oneover’ function is analysed and fabricated. This circuit, which is
implemented in a 2 pm n-well process, capitalises on the linear
region of the MOS transistor. The main contribution to nonlinearity is found to be produced by mobility degradation and
not by higher order terms of V,. Hence, the nonlinearity
appears as a constant which is easily cancelled. This circuit
does not require high degrees of component matching because
any offsets can easily be cancelled. The circuit operates with 8
bit accuracy and is mostly limited by pick-up noise. It has
been used in a tracking system where the target velocity is
inversely proportional to an integrated pulse width.
0IEE 1993
12th July 1993
R. Etienne-Cummings, R. Hathaway and J. Van der Spiegel
(Department of Electrical Engineering, Uniuersity of Pennsylvania, MO
S. 33rd St., Philadelphia, PA 19104, USA)
References
GREGONAN, R., and TEMES, T. c.: ‘Analog MOS integrated circuits
for signal processing’(Wiley and Sons, New York, 1986)
M.: ‘Four-transistor continuous-time MOS transconductor’, Electron. Lett., 1987,23, pp. 1099-1100
3 KHACHAB, N. I., and ISMAIL, M.: ‘MOS multiplier/divider cell for
analogue VLSI’, Electron. Lett., 1989,25,pp. 1550-1552
4 m ~ z o uc.,
, LIDGEY, F. I., and HAIGH, D. G . (Eds.): ‘Analogue IC
design: the current-mode approach (Peter Pereginus Ltd.,
London, 1990)
1
2 ISMAIL,
reader is referred to this article to see the flexibility of these
new algorithms. We expect that in one form or another these
algorithms will become the standard technique for decoding
RS codes. The solution technique presented here (and henceforth called ‘the algorithm’) is similar to that in Reference 1
and ‘algorithm 11’, in Reference 2, but it is not identical to
these. It is straightforward to implement, and the mathematical justification presented here is the most direct known to the
authors.
The algorithm finds a pair of polynomials P(x), Q(x) over
some field F, satisfying the key equation
yi Q(xJ = P(xi)
for i
=
1, ..., m
with
where m is a given positive integer, where the xi are given
distinct elements in F, and where the yi are given elements in
F. (Here [ k ] denotes the integer part of k.) Actually there is a
slightly tighter restriction on the degrees of the polynomials,
discussed in the final Section.
Algorithm: The algorithm generates parallel sequences of
polynomials P i x ) , Qxx), K(x), Fi’(x) so that P,(x) and Q.(x)
solve eqn. 1. In the following, the notation ( P , Q), denotes a
two-element vector with components P,(x), Q i x ) . Moreover J
and i are integers, and d and c are elements of the underlying
field F. A C-like syntax is used.
J = 0; Po(x) = 0 ; Qo(x)= I ;Vo(x)= 1;W,(x)= 1 ;/*initialise */
for(i = 1; i s m ; i++){/*loop on i from 1 t o m * /
if((d = y i Q i - l ( x i )- P i - , ( x i ) ) = =O)/*discrepancy at x i * /
{ ( V , W)i = ( X - x X V , mi- 1; ( P , Q)i = ( P , Q ) i - 1;
J=J+I;}
else {/* if d # 0 */ ( P , Q)i = ( x - xiXP, Q ) i c=CviW-i(xJ- K - i ( x i ) ) / d ; ( V ,w ) i = ( V , mi-1
- c(P, Q ) i - 1 ;
else J = J - 1;} /*
if (J= =0) swap ( V , W), and ( P ,
end d # 0 * /
)/*end of loop on i */
,;
Expressions for the maximal degrees of the polynomials
involved are given in the final Section; these may be useful in
the implementation of this algorithm.
ALGORITHM FOR SOLVING THE
WELCH-BERLEKAMP KEY-EQUATION, WITH
A SIMPLIFIED PROOF
W. G. Chambers, R. E. Peile, K. Y.Tsie and N. Zein
Indexinn terms: Decodina, Reed-Solomon codes
An alternative technique due to Welch and Berlekamp for
decoding Reed-Solomon codes has a key equation different
in form from the key equation solved by the conventional
BerlekampMassey algorithm or by the so-called Euclidean
algorithm. The Letter presents an algorithm for solving the
key equation which has a simple structure and which is
readily shown to work.
Introduction: The Welch-Berlekamp algorithm [I, 21 is an
improved technique for decoding Reed-Solomon (RS) and
related codes. It requires fewer computations than the classical
BerlekampMassey algorithm, especially when the average
error rate is kept well within the capabilities of the code; it
employs a key equation of a significantly different form. The
derivation of the key equation has recently been discussed in
Reference 3 but not its algorithmic solution and proof. We fill
these gaps in this Letter. Recently another algorithm has been
published which appears to be equivalent to the WelchBerlekamp algorithm in how it can be used [4], and the
1620
Justification: We start with some definitions: For r 2 0 let R,
den’ote a set of points with integer Cartesian co-ordinates (a,
b) satisfying - 1 5 a s r l / [ r / 2 ] , - 1 I b $ [ r / 2 ] ; moreover
(-1, -1) is excluded. We also define the ‘line sets’ L, as
R, - R,- 1, that is the set of all points in R, not in R,- 1. We
take Lo as R,. The sets Lo-L, are illustrated in Fig. 1, and
their union is R, . The polynomial pair (P(x), Q(x)) is said to
be at the point (deg P(x), deg Q(x)), where we take deg 0 as
-1, and is said to lie in any set containing this point. It is
called an r solution if it satisfies yiQ(xi) = P(xJ for i = 1 to r
without both P(x) and Q(x) being identically zero. (For r = 0
any polynomial pair is an r solution.) It is called a minimal r
solution either if P and Q are relatively prime (i.e. they have
no polynomial common factors) or if removing any polynomial common factor from P and Q stops its being an r
solution. A factor that is simply a field element is called a
scalar factor.
Next we need a uniqueness theorem:
-
Theorem 1 :
(i) there is at most one minimal r solution in R,
(ii) any other r solution in R, is a (polynomial) multiple of it
Proof of theorem I : Suppose that there are two minimal r
solutions ( P . Q ) and ( X , Y ) in R, which are not simply scalar
multiples of each other; then the polynomial P Y - Q X has r
roots, vanishing at x I , .. ., x,; however, its degree must be less
than r, and so it vanishes. Therefore P Y equals Q X . Next let
ELECTRONICS LETTERS 2nd September 1993 Vol. 29 No. 18
~~
-
A ( x ) be the HCF (highest common factor) of P and Q so that
P = A P and Q = A Q with P and Q‘ relatively prime. Substituting into P Y = Q X and cancelling A we obtain P Y = Q X
so that Q is a factor of P’Y and hence of Y ; it follows that
Y = B Q , X = B P for some polynomial B(x). Let C(x) be the
HCF of A and E ; then by the Euclid algorithm we can find
polynomials F(x) and G(x) so that F A GB = C. It is then
readily seen that (CP’, C Q ) = F . ( P , Q ) G . ( X , Y) is an r
solution. Assume without loss of generality that deg A t deg
E ; then C is a factor of A with deg C < deg A so that ( P , Q ) is
not minimal, and we therefore have a contradiction. Thus
apart from scalar multiples there is at most one minimal r
solution in R,. This proves the first part of the theorem. The
second part is a direct consequence: A second r solution in R,
cannot be minimal and its reduction must give the unique
minimal r solution in R,.
We are now ready for the main argument, which proceeds
by induction. The inductive hypothesis is as follows: For some
value r 1 of i at the top of the loop on i we assume:
+
+
+
(i) ( P , Q), lies in L,(ii) ( P , Q), is an r solution
(iii) (P, Q). is a minimal r solution
(iv) ( V , W, lies in L+J+
verifying assumption (iii). The argument is by contradiction. If
(P,Q),. = ( P . Q ) , + l is not minimal then by removing a poly-
+
nomial common factor we obtain an (r 1) solution ( X , Y )
lying in R,. Thus we have two r solutions in R,, that is (X,Y )
and (P, Q),. Thus by theorem 1 one must be a (polynomial)
multiple of the other and so (P,
and ( P , Q), are at points
in Fig. 1 joined by a line of slope 1. However, the swap puts
(P,
on a line-set L,+ while ( P . Q), lies on L,, and as Fig.
1 shows there is no line of slope 1 joining a point in L, to one
in L,,,.
e),+
e),+
Final remarks: As far as the maxima of the degrees of the
polynomials are concerned we note that because ( P , Q), lies in
L,-J it also lies in R,-, so that deg P, < r - J - 1 - [(r
- 4/21 and deg Q, s [(r - J)/2]. Similarly we find deg V, < r
+ J - [(r + J + 1)/2] and deg W, < [(r J 1)/2]. Moreover (P, Q), lies in R,_J which is a subset of R, so that deg
P , Im - 1 - [m/2], deg Q , < [m/2], as claimed in eqn. 2.
In decoding applications we know by other means [3] that
provided the number of errors t satisfies 2t 5 m there is a
minimal solution to eqn. 1 satisfying deg P < deg Q It. This
is a minimal m solution lying in R, and so by theorem 1 it is
the same as the solution found by the algorithm just
described, apart from a scalar multiple.
+ +
0IEE 1993
(v) (V, W), is an r solution (not necessarily minimal).
Evidently these assumptions are trivially obeyed for i = 1
when J = 0 and r = 0).At the bottom of the loop new polynomial pairs ( P , Q),.and (V,
with r’ = r 1 and a new
value J’ of J have been found. We must verify that the above
assumptions are still true when r’ and J’ have replaced r and
J. There are three mutually exclusive possibilities:
wr.
+
+
(1) The first is when d = 0; then J’ = J 1 and assumption (i)
above is readily verified because ( P , Q),. = ( P , Q), and
r ‘ - J ’ = r - J . Verifying the other assumptions is also
straightforward.
(2) The second case is when d # 0 with J > 0, so that
J‘ = J - 1. The main difficulty is in checking assumption (iv).
Updating (V,W) gives ( V , W),, = ( V , W). - c(P,
where ( P ,
Q ) , lies in L. with U = r - J , and where (V, W), lies in L, with
s = r + J + 1. Now s is odd if U is even and vice versa, and
also s - U is not less than 3. (Typical examples of L, and L,
are L, and L, in Fig. 1.) The outcome is decided by the
degrees of the polynomials to be added. The degree of the sum
of two polynomials with unequal degrees is the greater of
these degrees, but if these degrees are equal then the degree of
the sum can be less as leading terms may cancel.
(3) The third case is when d # 0 with J = 0; then J’ equals 0
also and the ‘swap’ takes place. The main difficulty here is
tb
28th July I993
of Electronic
and Electrical Engineering, King’s College London, Strand, London
WC2R ZLS, United Kingdom)
R. E. Pede (Racal Research Ltd., Worton Drive, Worton Grange Industrial Estate, Reading, Berks RGZ OSB, United Kingdom)
W.G. Chambers, K. Y. Tsie and N. Zein (Department
References
L., and BERLEKAMP, E. R.: ‘Error correction for algebraic
block codes’. US Patent 4 633 470, September 1983
2 LIU, T. H.:‘A new decoding algorithm for Reed-Solomon codes’.
PhD Thesis, University of Southern California, Los Angeles, CA,
1
WELCH,
1984
3 MORI], M., and UAHARA,
M. : ‘Generalized key-equation of remainder decoding algorithm for Reed-Solomon codes’, IEEE Trans.,
1992, IT-% pp. 1801-1807
4 SORGER, U. K.: ‘A new Reed-Solomon code decoding algorithm
based on Newton’s interpolation’, IEEE Trans., 1993, IT-39, pp.
358-365
EFFECT OF ION IMPLANTED GERMANIUM
PROFILE ON THE CHARACTERISTICS OF
Si,-,Ge,/Si
HETEROJUNCTION BIPOLAR
TRANSISTORS
K. Grahn, Z. Xia, P. Kuivalainen, M. Karlsteen and
M. Willander
Indexing terms: Transistors, Bipolar devices, Semiconductor
devices and materials
L1
L3
L5
An optimum profile for Ge ion implantation in SiGe/Si heterojunction bipolar transistors is determined by using a twodimensional simulator code for advanced semiconductor
devices. The simulation code is based on a two-dimensional
drift-diffusion model for heterostructure degenerate semiconductors with nonparabolicity included in the energy hand
structure. The model allows accurate simulations of carrier
transport in short base devices. The simulation results indicate that for high current gain the Ge profile maximum must
be close to the base-collector junction, and that the unavoidable tail of the implanted germanium in the collector region
does not deteriorate the gain.
L7
F33/11
Fig. 1 Line sets L, of points in plane with integer Cartesian coordinates
These co-ordinates are the degrees of polynomials in polynomial
pairs; the set R, is readily visualised as the union of Lo, . .., L,
Zntroduction: Pseudomorphic Si, - .GeJSi heterojunction
bipolar transistors (HBTs) are of increasing interest due to
their excellent high frequency and high current capabilities.
ELECTRONICS LETTERS 2nd September 1993 Vol. 29 No. 18
1621
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