EE564/CSE554: Error Correcting Codes Spring 2018 Week 3: January 22-26, 2018 Lecturer: Viveck R. Cadambe Scribe: Yu-Tse Lin
Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publications. They may be distributed outside this class only with the permission of the Instructor.
3.1 Basics of Linear Algebra
3.1.1 Abelian Group
(G, ∗) is a group if it satisfies the axioms:
1. Closure: a ∗ b ∈ G ∀a, b ∈ G
2. Associativity: a ∗ (b ∗ c) = (a ∗ b) ∗ c
3. Identity: ∃e, a ∗ e = e ∗ a = a∀a
4. Inverse: ∀a, ∃a−1, a ∗ a−1 = e
Moreover, (G, ∗) is an Abelian group if it also satisfies
5. Commutativity (Abelian): a ∗ b = b ∗ a
3.1.2 Field (F, +, ·)
(F, +, ·) is a field if it satisfies:
• (F, +) is an Abelian group
• (F − {0}, ·) is an Abelian group, where 0 is the identity in (F, +).
• Distributive law: a · (b + c) = a · b + a · c
A field is called finite field if F is a finite set. We will prove this theorem later in the course.
Theorem 3.1 (Zq, +, ×), where + and × are performed modulo q, is a finite field if and only if q is a prime.
3-1 3-2 Week 3: January 22-26, 2018
3.1.3 Vector Space
V is a vector space over field (F, +, ·), where + is an addition operation over V and · : F × V → V is a scalar multiplication operation if it satisfies:
1.( V, +) is an Abelian group,
2. Distributive law: α · (~v1 + ~v2) = α · ~v1 + α · ~v2, where · is scalar multiplication.
Recall some linear algebra concepts that will be used in the course:
• Linear independence: ~v1,~v2, ...,~vn are said to be linearly independent if
α1~v1 + α2~v2 + ... + αn~vn = 0 ⇐⇒ α1 = α2 = ... = αn = 0
• Span: The span of vectors is the set of all finite linear combinations of the vectors.
• Basis: A basis B of a vector space V over a field F is a maximal spanning set. Equivalently, it is a linearly independent subset of V that spans V .
• Dimension: The dimension of a vector space is the number of vectors in any basis for the space.
Note that F n is n-dimensional vector space over field F .
3.2 Linear Codes
An (n, k) linear code C, over a finite field F , is a k dimensional subspace of Fn. |C| = |F|k. Importantly, a linear combination of codewords is also a codeword in a linear code.
3.2.1 Generator Matrix of Linear Code C
A generator matrix G is in the form that ~g1 ~g2 G = . . ~gk and ~g1, ~g2, ...,~gk are 1 × n vectors that form a basis for the space; note that these vectors are linearly independent codewords. Dimension: k × n. Encoding: ~x = ~mG.
3.2.1.1 Examples 1. Repetition Codes: G1×n = 1 1 ... 1 Week 3: January 22-26, 2018 3-3