Scrambling¶

Scrambling as a channel coding step masks transmitted bits by a pseudo-random sequence known at both receiver and transmitter in order to prevent long sequences of identical bits. Therefore, most scrambling coding operations do not introduce redundancy to the scrambled bit blocks, i.e. the code rate is usually \(R = 1\).

class PseudoRandomGenerator(init_sequence, offset=1600)[source]¶

Bases: object

A generator for pseudo-random bit sequences.

Generators with identical initialization will output identical random sequences. Implements pseudo-random generator as described in the 3GPP standard for Physical Channels and Modulation[1].

Parameters:

init_sequence (numpy.ndarray) – A sequence of 31 bits initializing the generator.
offset (int) – Gold sequence parameter controlling the sequence offset.

generate()[source]¶

Generate the next bit within the pseudo-random sequence.

Returns:: The generated bit.
Return type:: int

generate_sequence(length)[source]¶

Generate a new sequence of random numbers.

Parameters:: length (int) – Length of the sequence to be generated.
Return type:: ndarray

Returns: A numpy array of dimension length containing a sequence of pseudo-random bits.

reset()[source]¶

Resets the gernator to its default state.

This implies reverting the queues back to their original state (at rng position n = 0).

Return type:: None

class Scrambler3GPP(seed=None)[source]¶

Bases: Encoder, Serializable

Scrambler channel coding in the physical up- and down-link standard of the 3GPP.

See section 7.3.1.1 of the respective technical standard Physical Channels and Modulation[1] for details.

Parameters:: seed (ndarray | None) – Seed used to initialize the scrambling sequence generation. Must contain a sequence of bits.

classmethod Deserialize(process)[source]¶

Deserialize an object’s state.

Objects cannot be deserialized directly, instead a Factory must be instructed to carry out the deserialization process.

Parameters:: process (DeserializationProcess) – The current stage of the deserialization process. This object is generated by the Factory and provides an interface to deserialization methods supporting multiple backends.
Return type:: Scrambler3GPP
Returns:: The deserialized object.

decode(code)[source]¶

Decodes a single block of bits.

Bit decoding routine during data reception, decoding a block of \(L_n\) code bits into a block of \(K_n\) data bits.

Parameters:: encoded_bits – A numpy vector of \(L_n\) code bits, representing a single code block to be decoded.
Return type:: ndarray

Returns: A numpy vector of \(K_n\) bits, representing a single data block.

Raises:: ValueError – If the length of encoded_bits does not equal code_block_size().

encode(data)[source]¶

Encodes a single block of bits.

Bit encoding routine during data transmission, encoding a block of \(K_n\) input bits into a block of \(L_n\) code bits.

Parameters:: bits – A numpy vector of \(K_n\) bits, representing a single bit block to be encoded.
Return type:: ndarray

Returns: A numpy vector of \(L_n\) bits, representing a single code block.

Raises:: ValueError – If the length of bits does not equal bit_block_size().

serialize(process)[source]¶

Serialize this object’s state.

Objects cannot be serialized directly, instead a Factory must be instructed to carry out the serialization process.

Parameters:: process (SerializationProcess) – The current stage of the serialization process. This object is generated by the Factory and provides an interface to serialization methods supporting multiple backends.
Return type:: None

property bit_block_size: int¶

Data bit block size of a single coding operation.

In other words, the number of input bits within a single code block during transmit encoding, or the number of output bits during receive decoding. Referred to as \(K_n\) within the respective equations.

property code_block_size: int¶

Code bit block size of a single coding operation.

In other words, the number of input bits within a single code block during receive decoding, or the number of output bits during transmit encoding. Referred to as \(L_n\) within the respective equations.

class Scrambler80211a(seed=None)[source]¶