# Outline. MSRI-UP 2009 Coding Theory Seminar, Week 2. The definition. Link to polynomials

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1 Outline MSRI-UP 2009 Coding Theory Seminar, Week 2 John B. Little Department of Mathematics and Computer Science College of the Holy Cross Cyclic Codes Polynomial Algebra More on cyclic codes Finite fields June 22-25, 2009 BCH codes designer cyclic codes The definition Link to polynomials Many codes that are used in practice have even more algebraic structure than the linear codes we have already seen. The cyclic shift π : F n 2 Fn 2 is the linear mapping defined by π(x 1,..., x n 1, x n ) = (x n, x 1,..., x n 1 ). Definition A linear code C is said to be a cyclic code if π(c) = C (that is, if the cyclic shift of every codeword is another codeword). Note: cyclic codes can be specified with less information. To study cyclic codes, we will introduce a polynomial form for the codewords: Given u = (u 1,..., u n ), we consider the polynomial u(x) = u 1 + u 2 x + + u n x n 1. Why do we do this? Mainly because the cyclic shift seems to be closely related to basic important operations on polynomials: The ordinary shift corresponds to x u(x) = u 1 x + + u n 1 x n 1 + u n x n. Then, to cycle the u n x n back to the start, we could divide by 1 + x n and take the remainder.

2 Algebra of polynomials Definition The set of all polynomials in the variable x with coefficients in a field F is denoted F[x]. We can add and multiply polynomials in F[x] as usual. All the field axioms hold except that some nonzero polynomials have no multiplicative inverses. We say F[x] is a commutative ring with (multiplicative) identity. Polynomial division Another very important aspect of the algebra of polynomials is the existence of a division algorithm for polynomials. Theorem (Division Algorithm) Let f (x) and g(x) 0 be in F[x]. There exist unique polynomials q(x) ( quotient ) and r(x) ( remainder ) such that f (x) = q(x)g(x) + r(x) and either r(x) = 0 or deg(r(x)) < deg(g(x)). If r(x) is the remainder on division of f (x) by g(x), we will write f (x) r(x) mod g(x).

3 Division algorithm The proof of the existence part of the theorem consists of the usual polynomial long division process from high school algebra. In procedural notation: input: f,g output: q,r r:=f; q:=0; while deg(g) <= deg(r) do q := q + in(r)/in(g); r := r - (in(r)/in(g))g; end while (where in(p) is the highest degree term in p) Division example Take g(x) = x 2 + x + 1 and f (x) = x 7 + x 6 + x and divide g into f (taking coefficients in F = F 2 it s amazing how simple the computations are in this case!) [Work out on board] The results are q(x) = x 5 + x 3 + x + 1 and r = 0. Note that this says g divides f in this case: x 7 + x 6 + x = (x 5 + x 3 + x + 1)(x 2 + x + 1). We write g f for the assertion g divides f (or equivalently f = qg for some q F[x].

4 A consequence of division Theorem Let I F[x] be any subset with the properties that f, g I f + g I, and f I, q F[x] qf I Then I = g = {qg q F[x]} for some g I. (Such sets are called ideals in the ring F[x] in abstract algebra; the theorem claims that any such set is generated by a single polynomial g(x).) Proof of the theorem Proof: If I = {0}, then we can take g = 0. If I contains nonzero polynomials, let g be any nonzero polynomial in I of minimal degree. If f I is any other polynomial, divide g into f to yield f = qg + r where either r = 0, or r is nonzero with deg(r) < deg(g). We claim that the second case cannot happen. Rearranging gives r = f qg I since f, g I. If r 0, then we get a contradiction to the choice of g.

5 Polynomial gcds Definition Let f, g F[x]. We say d = gcd(f, g) if d is a polynomial with leading coefficient 1 such that d f, d g, and if c is any other polynomial with c f and c g, then c d. (Equivalently, we could require d to be a nonzero divisor of maximal degree.) More on polynomial gcds The polynomial d = gcd(f, g) is unique (because of the requirement on the leading coefficient). d = gcd(f, g) can be computed by factoring f, g F[x] and finding the highest common factor. There is also a more efficient method called the Euclidean algorithm, based on division, that we will discuss next.

6 Euclidean algorithm for the gcd (Assuming deg(f ) deg(g)), perform divisions as indicated, until r m r m 1 : f = q 0 g + r 1 g = q 1 r 1 + r 2 r 1 = q 2 r 2 + r 3. r m 2 = q m 1 r m 1 + r m r m 1 = q m r m + 0 Note that the degrees of the r i are strictly decreasing. The last nonzero remainder r m is gcd(f, g). First Euclidean algorithm example Take f (x) = x 4 + x 2 + x + 1 and g(x) = x 3 + x 2. What is gcd(f, g)? We form the remainder sequence as on the last slide: x 4 + x 2 + x + 1 = (x + 1)(x 3 + x 2 ) + x + 1 x 3 + x 2 = x 2 (x + 1) + 0. Hence the final nonzero remainder in this case is the first one, d = x + 1. We can see here that f = (x 3 + x 2 + 1)(x + 1) and g = (x 2 )(x + 1) so x + 1 is a common divisor. Moreover, the only divisors of x + 1 are 1, x + 1, so x + 1 must be the gcd.

7 Another characterization of the gcd The easiest way to explain why the Euclidean algorithm works is to use another characterization of the gcd. Proposition Let f, g F[x]. Then gcd(f, g) is the nonzero polynomial of least degree (and leading coefficient 1) in the set: f, g = {Af + Bg A, B F[x]}. (In particular, the polynomial d = gcd(f, g) = Af + Bg for some A, B F[x]. We will see a way to find such polynomials A, B later.) Why does the Euclidean algorithm work? Sketch of argument: The set f, g is an ideal in F[x] as in our previous theorem. From the remainder sequence, it is easy to see that f, g = g, r 1 = = r m, 0 = r m. Hence r m = gcd(f, g).

8 Generator polynomial of a cyclic code We now return to the case of a cyclic code and consider the set of all polynomials corresponding to the codewords. Definition Let C be a cyclic code. The generator polynomial of C is the (unique) nonzero polynomial of smallest degree in C. (The uniqueness is a consequence of taking F = F 2 ; we get something similar in general if we require the leading coefficient to be 1.) The proof that polynomial ideals are generated by a single polynomial shows that qg mod x n + 1 represents a codeword for all q F 2 [x]. Consequences Theorem Let g be the generator polynomial for a cyclic code C, and assume that deg(g) = n k. g(x) divides x n + 1. u(x) is a codeword if and only if u(x) = q(x)g(x) for some q(x) of degree < k. The codewords corresponding to {g(x), xg(x), x 2 g(x),..., x k 1 g(x)} form a basis for C, so dim(c) = k. Proof: The second part follows by division; the third follows since these polynomials have distinct degrees, hence must be linearly independent.

9 Proof, continued We must show that if C is a cyclic code with generator polynomial g(x), then g(x) x n + 1. The codewords all have the form u(x) = q(x)g(x) mod x n + 1, so for each u(x) we have an equation u(x) = q(x)g(x) + s(x)(x n + 1) for some s(x). But we can write any u(x) as a multiple of g(x), and this implies g(x) (x n + 1) as claimed. Smallest cyclic code Given u F n 2, we can ask: What is the smallest cyclic code containing u? The answer comes by looking for the generator polynomial of the code It must be a polynomial that divides both u(x) and x n + 1, It must have maximum possible degree among polynomials satisfying the first condition (to get the smallest code) Hence, we get g(x) = gcd(u(x), x n + 1). Hence we can find g(x) by the Euclidean algorithm.

10 An example Find the generator polynomial for the smallest cyclic code containing the word (n = 6). We want gcd(1 + x 2 + x 3, 1 + x 6 ). Forming the remainder sequence, x = (x 3 + x 2 + x)(x 3 + x 2 + 1) + (x 2 + x + 1) x 3 + x = (x)(x 2 + x + 1) + x + 1 x 2 + x + 1 = (x)(x + 1) + 1. Hence gcd(1 + x 2 + x 3, 1 + x 6 ) = 1 (we say the polynomials are relatively prime). It follows that g = 1, so C = F 6 2 is the trivial code consisting of all words of length 6. Example, concluded We can also see the last statement here as follows. If C is cyclic, then all the cyclic shifts of u = must also be in C. In particular, these words are all in C: and u = , u + π(u) = , u + π 2 (u) = , π 3 (u + π 2 (u)) = Hence = C Hence π 5 (000110) = C So, finally, u = C.

11 Generator matrices for cyclic codes Today we will continue our study of cyclic codes by considering generator matrices for these codes, parity-check matrices for these codes, how to construct all cyclic codes of a given block length n. Generator matrices From our theorem at the end of class yesterday, we know that if g is a generator polynomial for a cyclic code C, and deg(g) = n k then {g(x), xg(x),..., x k 1 g(x)} is a basis for C. This gives a way to write down a generator matrix for C immediately we simply take the vector of coefficients of g, make that the first row in G, then shift the first row to get the other rows.

12 Generator matrix example Let C be the cyclic code with block length n = 7 and generator polynomial g(x) = x 3 + x (check x = (x 3 + x 2 + 1)(x 3 + x + 1)(x + 1), so that g(x) (x 7 + 1). Then G = (Note k = 4 since n = 7 and deg(g) = 3. Also, note how the first row determines the rest of the matrix we don t actually need the whole matrix in this case!) Parity-check matrices H for a cyclic code can be constructed by the method we discussed last week (Algorithm 2.5.7). However, that method does not use the fact that the code is cyclic, so it does not show an important pattern. By results from yesterday, w(x) represents a codeword of C with generator g(x) if and only if g(x) w(x). Compute r i = x i mod g(x) for i = 0,..., n 1 and put the vectors of coefficients of r i as rows in an n n k matrix H. Then a 0 + a 1 x + + a n 1 x n 1 is a codeword if and only if (a 0,..., a n 1 )H = 0. It follows that H is a parity-check matrix for C.

13 Parity-check matrix example Let C be the cyclic code from before with g(x) = 1 + x 2 + x 3 and n = 7. We compute 1 mod g(x) = 1, x mod g(x) = x, x 2 mod g(x) = x 2, x 3 mod g(x) = x 2 + 1, x 4 mod g(x) = x 2 + x + 1, x 5 mod g(x) = x + 1, x 6 mod g(x) = x 2 + x. Hence as on the last slide: H = Does this matrix look familiar (perhaps after permuting the rows)??

14 Comments on this example Note that the 7 rows of the matrix H are all the nonzero vectors of length n k = 3. Hence, this cyclic code is a Hamming [7, 4, 3] code. The codeword entries are ordered differently than we saw before, though. In general, two codes C and C are said to be equivalent if there is some fixed permutation σ S n that gives a 1-1 correspondence between words in C and words in C. Equivalent codes have the same n, k, d, so they are in effect equivalent for most coding-theoretic purposes. Finding all cyclic codes of length n Now we turn to the problem of determining all cyclic codes of a given length. Equivalently, we need to understand the factorization of x n + 1 in F 2 [x], since a generator polynomial must be a divisor of x n + 1. With g(x) = 1, we obtain the code containing all words in F n 2. On the other hand, if g(x) = 0, then we obtain the code containing only the zero word. Both of these are cyclic codes, but rather uninteresting ones(!) We will say a cyclic code is proper if it is not one of these.

15 Finding cyclic codes by factorization Over F 2, since 2 = 0, we have the first year student s dream factorization a 2 + b 2 = (a + b) 2. Hence if n = 2 r s, where s is odd, then 1 + x 2r s = 1 2r + (x s ) 2r = (1 + x s ) 2r, and all the interesting stuff is going to come from the factorization of 1 + x s in F 2 [x]. Proposition If n = 2 r s with s odd, and 1 + x s has z irreducible factors, then there are (2 r + 1) z cyclic codes of length n. Example: n = 10 We have 10 = 2 5, so in our general formula, r = 1 and s = 5. The polynomial x = (x + 1)(x 4 + x 3 + x 2 + x + 1) and we can see the second factor is irreducible it has no roots in F 2, so no linear factors, and (x 2 +ax +1)(x 2 +bx +1) = x 4 +(a+b)x 3 +abx 2 +(a+b)x +1 so a = b = 1 from coefficient of x 2 but this does not work. Hence there are 3 2 = 9 factors: Write p = x + 1, q = x 4 + x 3 + x 2 + x + 1. Then the factors are 1, p, p 2, q, pq, p 2 q, q 2, pq 2, p 2 q 2.

16 Another method idempotents We will conclude today s lecture by discussing another method for finding all cyclic codes of length n. For simplicity now we restrict to the case n odd. Main reason for this is a connection with our next topic (general finite fields), but this method is also somewhat simpler than factorization of x n + 1. Theorem Every cyclic code contains a unique idempotent polynomial I(x) satisfying (I(x)) 2 I(x) mod x n + 1. I(x) generates the code. Proof of the theorem Proof: Let g(x) be the generator polynomial and let g(x)h(x) = x n + 1. Then gcd(g(x), h(x)) = 1 (this is where the hypothesis n odd is used). By the facts about polynomial ideals and the Euclidean algorithm, there exist A(x), B(x) such that A(x)g(x) + B(x)h(x) = 1. Multiply by A(x)g(x): (A(x)g(x)) 2 + A(x)B(x)(x n + 1) = A(x)g(x). This implies (A(x)g(x)) 2 A(x)g(x) mod x n + 1. So we take I(x) = A(x)g(x). I(x) generates C since gcd(i(x), x n + 1) = g(x).

17 Properties of idempotents If I, J are idempotents, then so are I + J (by the first-year student s dream ) and IJ. Let C j = {2 i j mod n i Z} (called the cyclotomic coset of j mod n), Then C j is finite (e.g. C 3 for n = 7 is C 3 = {3, 6, 5}). The polynomial I j = k C j x k is idempotent. (Example: (x 3 + x 6 + x 5 ) 2 = x 6 + x 12 + x 10 x 6 + x 5 + x 3 mod x ) Hence we can construct an idempotent for each cyclotomic coset mod n, then take linear combinations. Fact: These are all the idempotents, hence all the cyclic codes of length n. An example Question: What are all the cyclic codes of length n = 21? The distinct cyclotomic cosets mod 21 are C 0 = {0} C 1 = {1, 2, 4, 8, 16, 11}(= C 2 = = C 11 ) C 3 = {3, 6, 12} C 5 = {5, 10, 20, 19, 17, 13} C 7 = {7, 14} C 9 = {9, 18, 15} Corresponding idempotents: I 0 = 1, I 1 = x + x 2 + x 4 + x 8 + x 16 + x 11, etc.

18 Example, concluded Then, any linear combination I = a 0 I 0 + a 1 I 1 + a 3 I 3 + a 5 I 5 + a 7 I 7 + a 9 I 9 with a i F 2 is also an idempotent. The generator polynomials for the corresponding cyclic codes can be found by computing gcd(i(x), x ). For instance, the code with I(x) = I 1 (x) + I 9 (x) has g(x) = x 17 + x 15 + x 14 + x 10 + x 8 + x 7 + x 3 + x + 1. (The actual computations are somewhat tedious, though, so we will stop here!) Introduction So far, we have only considered the finite field F 2 and studied codes over F 2. The next steps we will take involve: Using the algebra larger finite fields F 2 r to construct designer cyclic codes with minimum distance as large as we like. Using the larger finite fields themselves as alphabets for codes. The main examples we will study here are the Reed-Solomon codes, a very important family with interesting properties and many practical applications.

19 Irreducible polynomials Irreducible polynomials are analogous to primes in Z. Definition A nonconstant polynomial h(x) F 2 [x] is said to be irreducible in F 2 [x] if the only divisors of h(x) in F 2 [x] are 1 and h(x) itself. The definition above needs to be modified slightly if the coefficient field of the polynomials includes nonzero scalars other than 1 in that case, the nonzero constants are also allowed as divisors (as are the nonzero constants times h(x)). Fact: F 2 [x] contains irreducible polynomials of all degrees r 1 (see this week s Discussions). Examples of irreducibles degree 1: x + 1 degree 2: x 2 + x + 1 degree 3: x 3 + x + 1, x 3 + x degree 4: x 4 + x + 1, x 4 + x 3 + 1, x 4 + x 3 + x 2 + x + 1 degree 5: six of them There are rather extensive tables of these in the literature.

20 Residues modulo a polynomial The remainders modulo a polynomial h(x) have natural sum and product operations coming from the sum and product on polynomials Sum: (a(x) mod h(x)) + (b(x) mod h(x)) = (a(x) + b(x)) mod h(x). Product: (a(x) mod h(x))(b(x) mod h(x)) = (a(x)b(x)) mod h(x). For all h(x), the corresponding remainders ( residue classes ) form a commutative ring with identity, called F 2 [x]/ h(x). If h(x) is not irreducible, though, this ring will not be a field, because it has zero divisors. If h(x) = a(x)b(x) with neither constant, then (a(x)b(x)) mod h(x) = 0 but a(x) 0 mod h(x) and b(x) 0 mod h(x). Fields from irreducible polynomials Theorem Let h(x) F 2 [x] be irreducible. Then the residue class ring F 2 [x]/ h(x) is a field. If deg(h(x)) = r, then F 2 [x]/ h(x) = 2 r. This will be clear in the examples we use, so we omit the complete proof. The claim about the order of the field follows by counting the possible remainders on division by h(x): a 0 + a 1 x + + a r 1 x r 1. There are 2 r such since a i F 2 all i.

21 An example a field with 8 elements Let h(x) = x 3 + x + 1, which is one of the irreducibles of degree 3 in F 2 [x]. By the theorem, F = F 2 [x]/ x 3 + x + 1 is a field with 8 elements. Let us describe its structure by giving addition and multiplication tables. The 8 elements of F are F = {0, 1, x, x + 1, x 2, x 2 + 1, x 2 + x, x 2 + x + 1} The sum operation is easy (just add coefficients mod 2). For instance: (x 2 + x + 1) + (x) = x The full table is given on the next slide. The addition table For typographical reasons, we write a = x 2 + x, b = x 2 + x + 1 to save space! x x + 1 x 2 x a b x x + 1 x 2 x a b x + 1 x x x 2 b a x x x a b x 2 x x + 1 x + 1 x 1 0 b a x x 2 x 2 x 2 x a b 0 1 x x + 1 x x x 2 b a 1 0 x + 1 x a a b x 2 x x x b b a x x 2 x + 1 x 1 0

22 An observation Before we write the multiplication table, let us notice one important pattern about the multiplication operation. Let s take powers of x mod x 3 + x + 1 and see what happens: 1 mod h(x) = 1, x mod h(x) = x, x 2 mod h(x) = x 2, x 3 mod h(x) = x + 1, x 4 mod h(x) = x 2 + x, x 5 mod h(x) = x 2 + x + 1, x 6 mod h(x) = x 2 + 1, x 7 mod h(x) = 1. Observation, continued Note what happened here the powers of x give all the nonzero elements of F. This means that the multiplicative group of F is cyclic, generated by x. x is called a primitive element of F. This says, among other things, that the multiplication table will be easy to write out if we represent each nonzero element as a power of x(!)

23 The multiplication table Using the observation, 0 1 x x 2 x 3 x 4 x 5 x x x 2 x 3 x 4 x 5 x 6 x 0 x x 2 x 3 x 4 x 5 x 6 1 x 2 0 x 2 x 3 x 4 x 5 x 6 1 x x 3 0 x 3 x 4 x 5 x 6 1 x x 2 x 4 0 x 4 x 5 x 6 1 x x 2 x 3 x 5 0 x 5 x 6 1 x x 2 x 3 x 4 x 6 0 x 6 1 x x 2 x 3 x 4 x 5 The big theorem on finite fields Theorem There are fields of all orders 2 r, r 1. Every finite field of order 2 r has primitive elements (φ(2 r 1) of them, in fact Euler φ-function). Every nonzero element of a field of order 2 r satisfies the polynomial equation z 2r = 0. Any two fields of order 2 r are isomorphic, so we will write F 2 r to denote the field of order 2 r. F 2 r F 2 s if and only if r s.

24 An example The proof is not especially difficult, but it would take us too far afield, so we omit it. Instead, we illustrate what it is saying by considering fields of size 16 = 2 4. Let us start by using the irreducible h(x) = x 4 + x + 1 to construct the field. The elements are the remainders on division by h(x), so for all choices of a i F 2. a 0 + a 1 x + a 2 x 2 + a 3 x 3 x is primitive Compute the powers of x mod h(x): 1 1 mod h(x) x 8 x mod h(x) x x mod h(x) x 9 x 3 + x mod h(x) x 2 x 2 mod h(x) x 10 x 2 + x + 1 mod h(x) x 3 x 3 mod h(x) x 11 x 3 + x 2 + x mod h(x) x 4 x + 1 mod h(x) x 12 x 3 + x 2 + x + 1 mod h(x) x 5 x 2 + x mod h(x) x 13 x 3 + x mod h(x) x 6 x 3 + x 2 mod h(x) x 14 x mod h(x) x 7 x 3 + x + 1 mod h(x) x 15 1 mod h(x).

25 The polynomial z The previous computation shows x is primitive and x 15 = 1, so x = 0. Since every nonzero element of the field is a power of x, this means that every nonzero element of the field also satisfies the polynomial equation z = 0. If we factor z in F 2 [z], we see something interesting: z = (z+1)(z 2 +z+1)(z 4 +z 3 +z 2 +z+1)(z 4 +z+1)(z 4 +z 3 +1). That is, the factors are all the irreducibles of degree 1, 2, 4 (the divisors of 4). This fact actually implies the last two parts of the theorem as well. Example, continued F 2 4 contains roots of z 4 + z and z 4 + z 3 + z 2 + z + 1 as well. We would actually have obtained an isomorphic field starting from any one of the three irreducibles of degree 4. The factors z + 1 and z 2 + z + 1 have roots 1 F 2, and the elements of F 2 2 not contained in F 2, respectively. Hence we have copies of F 2, F 2 2 sitting as subfields of F 2 4. Caution: It is not always the case that a root of an irreducible h(x) of degree r is primitive for the field F 2 r. The roots of the degree 4 polynomial z 4 + z 3 + z 2 + z + 1 are 5th roots of unity (so not primitive 15th roots of 1).

26 Minimal polynomial of an element We will need the following notion. Definition Let α F 2 r. The minimal polynomial of α over F 2 is the nonzero polynomial of smallest degree in F 2 [z] having α as a root. Proposition The minimal polynomial of an element α is an irreducible polynomial in F 2 [x]. Proof: If m(z) = f (z)g(z) and m(α) = 0, then either f (α) = 0 or g(α) = 0. Example In F 2 4 constructed with h(x) = x 4 + x + 1 as above: The element 1 has minimal polynomial z + 1 The elements x 5, x 10 have minimal polynomial z 2 + z + 1 The elements x, x 2, x 4, x 8 have minimal polynomial z 4 + z + 1 The elements x 7, x 14, x 13, x 11 have minimal polynomial z 4 + z The elements x 3, x 6, x 12, x 9 have minimal polynomial z 4 + z 3 + z 2 + z + 1

27 Example, concluded For instance, if z = x 7 = x 3 + x + 1 (from before), then z 4 + z = x 13 + x = (x 3 + x 2 + 1) + (x 3 + x 2 ) + 1 = 0. The other roots of this irreducible z 4 + z come from a cyclotomic coset mod 15 as we discussed yesterday! C 7 = {7, 14, 13, 11}. Can you see why? Introduction BCH codes It is possible to make cyclic codes with any d provided n is large enough. We will see one construction today, the so-called BCH codes. The name comes from the names of the original developers of these codes Bose, Chaudhuri, and Hocquenghem. To warm up for the BCH codes, we return to the cyclic Hamming code we saw a couple of days ago.

28 Cyclic Hamming codes Theorem Let h(x) be a primitive irreducible polynomial of degree r (that is, the roots of h(x) are primitive elements of the field F 2 r = F 2 [x]/ h(x) ). Then the cyclic code C of length n = 2 r 1 with generator polynomial h(x) is a [2 r 1, 2 r r 1, 3] Hamming code. Proof: Write α = x in the field F 2 r. The powers of α give all the nonzero elements of the field. Proof, continued u(x) is a codeword if and only if h(x) u(x), which is true if and only if u(α) = 0. So if we write u = u 0 + u 1 x + + u 2 r 2x 2r 2, then 1 α (u 0 u 1... u 2 r 2). = 0. α 2r 2 Rewrite the entries in the column using the expansions of α i in terms of 1, x,..., x r 1. The resulting 2 r 1 r matrix is a parity check matrix for C, and its rows are all the nonzero vectors of length r in some order.

29 Generalizing to get larger d We will present a construction of BCH codes with minimum distance d 5 (actually = 5 with a bit more work), length n = 2 r 1 and k = 2 r 2r 1. You will see how to get d δ for any δ = 2t + 1 in the Discussion today. Let α be a primitive element of F 2 r, let m 1 (x) be the minimal polynomial of α, and let m 3 (x) be the minimal polynomial of α 3. Let g(x) = m 1 (x)m 3 (x) be the generator polynomial for a cyclic code of length n = 2 r 1. We claim that C has d 5. Some first observations First, note that the roots of m 1 (x) contain α, α 2, α 4 (powers contained in the cyclotomic coset C 1 ). Hence the roots of g(x) contain α, α 2, α 3, α 4 (a consecutive string of 4 powers of α). Hence the polynomial form of every codeword of C has roots containing the consecutive string α, α 2, α 3, α 4. This means that each codeword u = (u 0 u 1 u 2 r 2) satisfies the equation u H = 0 where H is the (2 r 1) 4 matrix over F 2 r on the next page.

30 The matrix H α α 2 α 3 α 4 H = α 2 (α 2 ) 2 (α 3 ) 2 (α 4 ) α 2r 2 (α 2 ) 2r 2 (α 3 ) 2r 2 (α 4 ) 2r 2 More on the matrix H H is not a parity-check matrix according to our definitions (entries not in F 2, and if we replace each α i by a vector in F r 2, the columns will be linearly dependent). But, the characterization of d in terms of linearly independent sets of the rows extends to this case. Proposition If all sets of 4 rows of H are linearly independent over F 2 r, then d 5. Proof: If d 4, then there is some codeword of weight 4, which gives a linear dependence on a set of 4 rows in H.

31 A special determinant So consider the determinant of the 4 4 submatrix of H in rows 1 i < j < l < m 2 r 1: α i (α 2 ) i (α 3 ) i (α 4 ) i det α j (α 2 ) j (α 3 ) j (α 4 ) j α l (α 2 ) l (α 3 ) l (α 4 ) l α m (α 2 ) m (α 3 ) m (α 4 ) m Special determinant, continued Using standard properties of determinants, we can factor α i out of row 1, α j out of row 2, etc. leaving 1 α i (α i ) 2 (α i ) 3 = α i+j+l+m det 1 α j (α j ) 2 (α j ) 3 1 α l (α l ) 2 (α l ) 3 1 α m (α m ) 2 (α m ) 3

32 Special determinant, continued We see that this is a 4 4 Vandermonde matrix (possibly transpose, depending on how you define Vandermondes). General form is 1 a a 2 a 3 V (a, b, c, d) = det 1 b b 2 b 3 1 c c 2 c 3 1 d d 2 d 3 The Vandermonde determinant We claim V (a, b, c, d) = (b a)(c a)(d a)(c b)(d b)(d c) (for a, b, c, d in any field F) Note that if a = b, etc. then the matrix has two equal rows, so the determinant is divisible by the product of the pairwise differences. The total degree is 6, so our formula for V (a, b, c, d) is correct up to a constant factor. The coefficient of d 3 c 2 b is +1 in V (a, b, c, d) and in the claimed formula. Hence the claim is proved.

33 Consequences The determinant of our Vandermonde matrix is nonzero because α i, α j, α l, α m are distinct elements of F 2 r. It follows that our code has d 5. What about k, the dimension? The dimension of the BCH code Going back to the definition of H, recall that the second and fourth columns come because we know other roots of the polynomial m 1 (x). So in fact we really only need the columns for α and α 3. If those are converted to binary vectors, we get a (2 r 1) 2r matrix whose columns are linearly independent. Hence, k = 2 r 2r 1. Finally, we see that r 4 is necessary to get a code of dimension > 1 here.

34 Summary Modulo some details, we have proved the following. Theorem Let r 4. There is a 2 bit error correcting BCH code of length n = 2 r 1 and k = 2 r 2r 1 with d = 5 and generator polynomial g(x) = m 1 (x)m 3 (x). For instance, with r = 5, we get a [31, 21, 5] code over F 2. (This is the best possible d for n = 31, k = 21 over F 2.) A simple algebraic decoding method for these codes is given in 5.5 in the text.

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