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In computing, a linearfeedback shift register (LFSR) is a shift register whose input bit is a linear function of its previous state.
The most commonly used linear function of single bits is exclusiveor (XOR). Thus, an LFSR is most often a shift register whose input bit is driven by the XOR of some bits of the overall shift register value.
The initial value of the LFSR is called the seed, and because the operation of the register is deterministic, the stream of values produced by the register is completely determined by its current (or previous) state. Likewise, because the register has a finite number of possible states, it must eventually enter a repeating cycle. However, an LFSR with a wellchosen feedback function can produce a sequence of bits which appears random and which has a very long cycle.
Applications of LFSRs include generating pseudorandom numbers, pseudonoise sequences, fast digital counters, and whitening sequences. Both hardware and software implementations of LFSRs are common.
The mathematics of a cyclic redundancy check, used to provide a quick check against transmission errors, are closely related to those of an LFSR.
The bit positions that affect the next state are called the taps. In the diagram the taps are [16,14,13,11]. The rightmost bit of the LFSR is called the output bit. The taps are XOR'd sequentially with the output bit and then fed back into the leftmost bit. The sequence of bits in the rightmost position is called the output stream.
The sequence of numbers generated by an LFSR or its XNOR counterpart can be considered a binary numeral system just as valid as Gray code or the natural binary code.
The arrangement of taps for feedback in an LFSR can be expressed in finite field arithmetic as a polynomial mod 2. This means that the coefficients of the polynomial must be 1's or 0's. This is called the feedback polynomial or reciprocal characteristic polynomial. For example, if the taps are at the 16th, 14th, 13th and 11th bits (as shown), the feedback polynomial is
The 'one' in the polynomial does not correspond to a tap – it corresponds to the input to the first bit (i.e. x^{0}, which is equivalent to 1). The powers of the terms represent the tapped bits, counting from the left. The first and last bits are always connected as an input and output tap respectively.
The LFSR is maximallength if and only if the corresponding feedback polynomial is primitive. This means that the following conditions are necessary (but not sufficient):
Tables of primitive polynomials from which maximumlength LFSRs can be constructed are given below and in the references.
There can be more than one maximumlength tap sequence for a given LFSR length. Also, once one maximumlength tap sequence has been found, another automatically follows. If the tap sequence, in an nbit LFSR, is [n, A, B, C, 0], where the 0 corresponds to the x^{0} = 1 term, then the corresponding 'mirror' sequence is [n, n − C, n − B, n − A, 0]. So the tap sequence [32, 7, 3, 2, 0] has as its counterpart [32, 30, 29, 25, 0]. Both give a maximumlength sequence.
Some example C code is below:
# include <stdint.h> int main(void) { uint16_t start_state = 0xACE1u; /* Any nonzero start state will work. */ uint16_t lfsr = start_state; unsigned bit; unsigned period = 0; do { /* taps: 16 14 13 11; feedback polynomial: x^16 + x^14 + x^13 + x^11 + 1 */ bit = ((lfsr >> 0) ^ (lfsr >> 2) ^ (lfsr >> 3) ^ (lfsr >> 5) ) & 1; lfsr = (lfsr >> 1)  (bit << 15); ++period; } while (lfsr != start_state); return 0; }
This LFSR configuration is also known as standard, manytoone or external XOR gates. The alternative Galois configuration is described in the next section.
Named after the French mathematician Évariste Galois, an LFSR in Galois configuration, which is also known as modular, internal XORs as well as onetomany LFSR, is an alternate structure that can generate the same output stream as a conventional LFSR (but offset in time).^{[2]} In the Galois configuration, when the system is clocked, bits that are not taps are shifted one position to the right unchanged. The taps, on the other hand, are XOR'd with the output bit before they are stored in the next position. The new output bit is the next input bit. The effect of this is that when the output bit is zero all the bits in the register shift to the right unchanged, and the input bit becomes zero. When the output bit is one, the bits in the tap positions all flip (if they are 0, they become 1, and if they are 1, they become 0), and then the entire register is shifted to the right and the input bit becomes 1.
To generate the same output stream, the order of the taps is the counterpart (see above) of the order for the conventional LFSR, otherwise the stream will be in reverse. Note that the internal state of the LFSR is not necessarily the same. The Galois register shown has the same output stream as the Fibonacci register in the first section. A time offset exists between the streams, so a different startpoint will be needed to get the same output each cycle.
Below is a C code example for the 16 bit maximal period Galois LFSR example in the figure:
# include <stdint.h> int main(void) { uint16_t start_state = 0xACE1u; /* Any nonzero start state will work. */ uint16_t lfsr = start_state; unsigned period = 0; do { unsigned lsb = lfsr & 1; /* Get LSB (i.e., the output bit). */ lfsr >>= 1; /* Shift register */ if (lsb == 1) /* Only apply toggle mask if output bit is 1. */ lfsr ^= 0xB400u; /* Apply toggle mask, value has 1 at bits corresponding * to taps, 0 elsewhere. */ ++period; } while (lfsr != start_state); return 0; }
Binary Galois LFSRs like the ones shown above can be generalized to any qary alphabet {0, 1, ..., q − 1} (e.g., for binary, q is equal to two, and the alphabet is simply {0, 1}). In this case, the exclusiveor component is generalized to addition moduloq (note that XOR is addition modulo 2), and the feedback bit (output bit) is multiplied (moduloq) by a qary value which is constant for each specific tap point. Note that this is also a generalization of the binary case, where the feedback is multiplied by either 0 (no feedback, i.e., no tap) or 1 (feedback is present). Given an appropriate tap configuration, such LFSRs can be used to generate Galois fields for arbitrary prime values of q.
The following table lists maximallength polynomials for shiftregister lengths up to 19. Note that more than one maximallength polynomial may exist for any given shiftregister length. A list of alternative maximallength polynomials for shiftregister lengths 432 (beyond which it becomes unfeasible to store or transfer them) can be found here: http://www.ece.cmu.edu/~koopman/lfsr/index.html
Bits  Feedback polynomial  Period 

n  
2  3  
3  7  
4  15  
5  31  
6  63  
7  127  
8  255  
9  511  
10  1023  
11  2047  
12  4095  
13  8191  
14  16383  
15  32767  
16  65535  
17  131071  
18  262143  
19  524287  
20168  [1]  
2786,1024,2048,4096  [2] 
LFSRs can be implemented in hardware, and this makes them useful in applications that require very fast generation of a pseudorandom sequence, such as directsequence spread spectrum radio. LFSRs have also been used for generating an approximation of white noise in various programmable sound generators.
The repeating sequence of states of an LFSR allows it to be used as a clock divider, or as a counter when a nonbinary sequence is acceptable as is often the case where computer index or framing locations need to be machinereadable.^{[4]} LFSR counters have simpler feedback logic than natural binary counters or Gray code counters, and therefore can operate at higher clock rates. However it is necessary to ensure that the LFSR never enters an allzeros state, for example by presetting it at startup to any other state in the sequence. The table of primitive polynomials shows how LFSRs can be arranged in Fibonacci or Galois form to give maximal periods. One can obtain any other period by adding to an LFSR that has a longer period some logic that shortens the sequence by skipping some states.
LFSRs have long been used as pseudorandom number generators for use in stream ciphers (especially in military cryptography), due to the ease of construction from simple electromechanical or electronic circuits, long periods, and very uniformly distributed output streams. However, an LFSR is a linear system, leading to fairly easy cryptanalysis. For example, given a stretch of known plaintext and corresponding ciphertext, an attacker can intercept and recover a stretch of LFSR output stream used in the system described, and from that stretch of the output stream can construct an LFSR of minimal size that simulates the intended receiver by using the BerlekampMassey algorithm. This LFSR can then be fed the intercepted stretch of output stream to recover the remaining plaintext.
Three general methods are employed to reduce this problem in LFSRbased stream ciphers:
Important LFSRbased stream ciphers include A5/1 and A5/2, used in GSM cell phones, E0, used in Bluetooth, and the shrinking generator. The A5/2 cipher has been broken and both A5/1 and E0 have serious weaknesses.^{[5]}^{[6]}
The linear feedback shift register has a strong relationship to linear congruential generators.^{[7]}
LFSRs are used in circuit testing, for testpattern generation (for exhaustive testing, pseudorandom testing or pseudoexhaustive testing) and for signature analysis.
Complete LFSR are commonly used as pattern generators for exhaustive testing, since they cover all possible inputs for an n input circuit. Maximum length LFSRs and weighted LFSRs are widely used as pseudorandom test pattern generators for pseudorandom test applications.
In builtin selftest (BIST) techniques, storing all the circuit outputs on chip is not possible, but the circuit output can be compressed to form a signature which later will be compared to the golden signature (of the good circuit) to detect faults. Since this compression is lossy, there is always a probability that a faulty output also generates the same signature as the golden signature and the faults can not be detected. This condition is called error masking or aliasing. This is accomplished by using a multipleinput signature register (MISR or MSR) which is a type of LFSR. A standard LFSR has a single XOR or XNOR gate where the input of the gate is connected to several "taps" and the output is connected to the input of the first flipflop. A MISR has the same structure, however, the input to every flipflop is fed through an XOR/XNOR gate. For example, a four bit MISR has a fourbit parallel output and a fourbit parallel input. The input of the first flipflop is XOR/XNORd with parallel input bit zero and the "taps." Every other flipflop input is XOR/XNORd with the preceding flipflop output and the corresponding parallel input bit. Consequently, the next state of the MISR is dependent on the last several states opposed to just the current state. Therefore, a MISR will always generate the same golden signature given that input sequence is the same every time.
To prevent short repeating sequences (e.g., runs of 0's or 1's) from forming spectral lines that may complicate symbol tracking at the receiver or interfere with other transmissions, linear feedback registers are often used to "randomize" the transmitted bitstream. This randomization is removed at the receiver after demodulation. When the LFSR runs at the same bit rate as the transmitted symbol stream, this technique is referred to as scrambling. When the LFSR runs considerably faster than the symbol stream, expanding the bandwidth of the transmitted signal, this is directsequence spread spectrum.
Neither scheme should be confused with encryption or encipherment; scrambling and spreading with LFSRs do not protect the information from eavesdropping. They are instead used to produce equivalent streams that possess convenient engineering properties to allow for robust and efficient modulation and demodulation.
Digital broadcasting systems that use linear feedback registers:
Other digital communications systems using LFSRs:
The German time signal DCF77, in addition to amplitude keying, employs phaseshift keying driven by a 9stage LFSR to increase the accuracy of received time and the robustness of the data stream in the presence of noise.^{[9]}
The Global Positioning System uses an LFSR to rapidly transmit a sequence that indicates highprecision relative time offsets.
LFSRs are also used in Communications System Jamming systems in which they are used to generate pseudo random noise to raise the noise floor of a target communication system.