This application claims the benefit of Russian Application No. 2010148337, filed Nov. 29, 2010 and is hereby incorporated by reference in its entirety.
The present invention relates to trellis decoding generally and, more particularly, to a method and/or apparatus for implementing a branch metrics calculation for multiple communications standards.
Turbo and convolutional codes are widely used forward error correction codes. Turbo codes were proposed by Berrou and Glavieux in 1993 and have been adopted in many communication standards such as Wideband-CDMA (WCDMA), Code Division Multiple Access 2000 (CDMA2000), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) and Digital Video Broadcasting-Return Channel via Satellite (DVB-RCS). The codes allow near optimal decoding with excellent performance approaching the Shannon limit for Additive White Gaussian Noise (AWGN) channels.
Conventional radix-4 decoding supports duo-binary turbo codes (adopted in WiMAX and DVB-RCS) and single-binary convolutional and turbo codes. Moreover, support for the duo-binary turbo codes implies two times faster decoding techniques than for single-binary codes at the expense of some additional circuit area. A problem with radix-4 decoding is a bottleneck in calculating the state metrics. A State Metrics Calculator (SMC) circuit performing add-compare-select operations experiences a bottleneck when implementing high-speed convolutional and turbo decoders. State metrics calculations cannot be easily pipelined because the state metrics computed at time instance t are used for computing the state metrics at time instance t+1. Therefore, radix-4 decoding increases the importance of the path through the SMC circuit. Another problem with radix-4 decoding is related with decoder universality (i.e., the ability to support many different convolutional and turbo codes in the same hardware). Since the trellises for the various codes are different, additional configuration logic (i.e., multiplexers) is commonly used in the SMC circuit to handle all of the trellises in a single design.
The present invention concerns a method for branch metric calculation in a plurality of communications standards. The method generally includes steps (A) to (C). Step (A) may calculate a plurality of sum values by adding a plurality of first values related to a plurality of information bits, a plurality of second values related to the information bits and a plurality of third values related to a plurality of parity bits. Step (B) may generate a plurality of permutated values by permutating the sum values based on a configuration signal. The configuration signal generally identifies a current one of the communications standards. Step (C) may generate a plurality of branch metrics values by adding pairs of the permutated values.
The objects, features and advantages of the present invention include providing a method and/or apparatus for implementing a branch metrics calculation for multiple communications standards that may (i) implement a configurable branch metrics calculator, (ii) avoid multiplexers in state metrics calculations, (iii) support multiple communications standards, (iv) implement a universal switch module and/or (v) occupy a low silicon area.
These and other objects, features and advantages of the present invention will be apparent from the following detailed description and the appended claims and drawings in which:
Some embodiments of the present invention generally concern a reconfigurable chip (or die) for decoding an input signal in accordance with two or more wireless communications standards. The wireless communications standards may include, but are not limited to, a Long Term Evolution (LTE) standard (3GPP Release 8), an Institute of Electrical and Electronics Engineering (IEEE) 802.16 standard (WiMAX), a Wideband-CDMA/High Speed Packet Access (WCDMA/HSPA) standard (3GPP Release 7) and a CDMA-2000/Ultra Mobile Broadband (UMB) standard (3GPP2). Other wired and/or wireless communications standards may be implemented to meet the criteria of a particular application.
Some embodiments of the present invention may relate to decoder universality where many different convolutional codes and turbo codes are supported in the same hardware. Instead of adding configuration logic to a State Metric Calculation (SMC) circuit, configuration logic may be added to a Branch Metric Calculation (BMC) circuit. The BMC circuit generally computes branch metrics and may be used with the SMC circuit in decoding. The BMC circuit may be readily pipelined. Hence, adding configuration logic to BMC circuit generally does not lead to a bottleneck. Moreover, implementations of some embodiments may utilize low silicon area and may be easily configured. Any rate (e.g., ⅓ rate) convolutional encoder with a given constraint length (e.g., up to 8) may be supported. Furthermore, a simple universal permutation 4×4-network may be used in the configuration logic to reduce the overall layout area.
The universal BMC circuit design generally includes a radix-4 universal branch metric calculation. The universal branch metric calculation may be used in both (i) Maximum-Logarithmic-MAP (Maximum A Posteriori) decoding techniques of turbo codes and (ii) Viterbi decoding techniques of convolutional codes. The universal branch metric calculations may also be used for high-speed and low-area implementations of multi-standard radix-4 decoders supporting turbo and convolutional decoding for most existing wireless standards, such as W-CDMA, CDMA2000, WiMAX and LTE.
Referring to
The signal IN may convey an information word received by the apparatus 100. The information word “d” (e.g., data to be transmitted) may be described by formula 1 as follows:
d=(d1, . . . , dk)ε{0,1}k (1)
where each diε{0,1} may be an information bit and parameter “k” may be an information word length. The apparatus 100 generally adds redundancy to the information word d and produces a codeword “c” in the signal OUT. Codeword c is generally illustrated by formula 2 as follows:
c=(c1, . . . , cn)ε{0,1}n (2)
where “n” is the codeword length and R=k/n may be a code rate.
For convolutional rate 1/s, the apparatus 100 may be defined by a generator matrix G. Generator matrix G is generally shown in formula 3 as follows:
G=[g(1)(D), . . . , g(s)(D)] (3)
where each g(i)(D) (e.g., formula 4)
may be a rational function in variable D over the binary field F2={0,1}. The elements a(i)(D), b(i)(D)εF2(D) may be polynomials in D with coefficients in F2 and a(i)(0)=b(i)(0)=1. When the apparatus 100 receives the signal IN carrying an infinite binary sequence (e.g., formula 5)
d=d1,d2, . . . , di, . . . (5)
the signal IN may be interpreted as a formal power series per formula 6 as follows:
d(D)=d1+d2D+ . . . +diDi−1+ . . . (6)
The apparatus 100 may generate multiple signals (e.g., P1 to PS). A combination of the signals P1 to PS may form the signal OUT. Each signal P1 to PS may carry a sequence (e.g., p(1) to p(s)) as shown in formulae 7 set as follows:
The sequences may be considered as formal power series and calculated as shown in formulae set 8 as follows:
The resulting codeword c may be represented by formula 9 as follows:
c=(p1(1), . . . , p1(s),p2(1), . . . , p2(s), . . . , pk(1), . . . , pk(s) (9)
where p(j) (e.g., formula 10)
p(j)=(p1(j), . . . , pk(j)) (10)
may be the j-th element created by the convolutional encoding. The word p(j) may be referred to as a parity word.
In the case of convolutional codes (CC) generally used in wireless standards, the channel encoding may not be systematic (e.g., the encoding may have a polynomial transfer matrix). In the case of convolutional turbo codes (CTC), the encoding may be systematic (e.g., the information word d may be a part of the codeword c).
Referring to
The circuit 104 may implement a Recursive Systematic Convolutional (RSC) encoder. The circuit 104 is generally operational to encode the information word d to generate the parity word p(1). The information word d may be received in the signal IN. The parity word p(1) may be presented in the signal P1. The encoding may be a recursive systematic convolutional encoding.
The circuit 106 may implement another RSC encoder. The circuit 106 is generally operational to encode a permuted word π(d) (e.g., formula 11)
π(d)=(dπ(1), . . . , dπ(k)) (11)
to generate the parity word p(2). The permuted word π(d) may be received in the signal PER from the circuit 108. The parity word p(2) may be presented in the signal P2. The encoding may also be a recursive systematic convolutional encoding. The circuit 106 may be a duplicate of the circuit 104 and perform the same encoding technique.
The circuit 108 may implement an interleaver circuit. The circuit 108 is generally operational to generated the permuted word π(d) by permutating the information word d. The information word d may be received in the signal IN. The permuted word π(d) may be presented to the circuit 106 in the signal PER.
Each standard LTE, W-CDMA/HSPA and WiMAX may include rate ⅓ turbo codes. In the WiMAX standard, the codeword c may be given by formula 12 as follows:
c=(d1,p1(1),p1(2), . . . , dk,pk(1),pk(2)) (12)
where n=3k and tail-biting may be utilized. In the LTE standard and the W-CDMA/HSPA standard, the codeword c is generally illustrated by formula 13 as follows:
c=(d1,p1(1),p1(2), . . . , dk,pk(1),pk(2),t1, . . . , t12) (13)
where n=3k+12 and the final several bits (e.g., 12 bits t1, . . . , t12) may be used for trellis termination. The trellis termination generally forces the apparatus 102 to an initial zero state. In the case of trellis termination, the actual code rate k/(3k+12) may be a little smaller than the rate ⅓.
In the above cases, the parity word p(1) in the signal P1 may convey the parity bits word obtained for an unpermuted information word d generated by the circuit 104. The parity word p(2) may be obtained for the permuted word π(d) generated by the circuit 108. An operation n may be a permutation on a set {1, 2, . . . , k} specified by an interleaver table of the standard.
A decoder is generally a device that receives vector of quantized Logarithm of Likelihood Ratios (LLR's) for each bit in the codeword c as received from a modulator. The modulator operation may be denoted by L(c). The decoder generally attempts to reconstruct the transmitted information word d. A decision of the decoder may be denoted by a {circumflex over (d)} per formula 14 as follows:
{circumflex over (d)}=({circumflex over (d)}1, . . . , {circumflex over (d)}k)ε{0,1}k (14)
Each value {circumflex over (d)}i may be called a hard decision for information bit {circumflex over (d)}i, where i=1 to k. Sometimes (e.g., in turbo equalization) the decoder may also generate soft decisions for the information and the parity bits. Such decoders may be called soft-input soft-output (SISO) decoders.
Referring to
A signal (e.g., LIN(D)) may be received by the circuits 122, 124 and 126a. A signal (e.g., LIN(P1)) may be received by the circuit 122. A signal (e.g., LIN(P2)) may be received by the circuit 124. The circuit 128a may generate a signal (e.g., LOUT(D)). A signal (e.g., LOUT(P1)) may be generated by the circuit 122. The circuit 124 may generate a signal (e.g., LOUT(P2)). A signal (e.g., STOP/CONT) may be generated by the circuit 132.
Turbo decoding may perform a number of computation cycles called full iterations. Each full iteration may include two half iterations. The turbo decoding process generally runs until either a maximum full iteration number (e.g., typical value is 8) is reached or one or more early stopping criterion is satisfied.
On each half iteration, the circuits 122 and 124 generally perform a Maximum A Posteriori (MAP) process explained below for one of the constitutive convolutional encoders RCS1 and RSC2 of a turbo encoder (see
Referring to
The signal IN may be received by the circuit 142. The circuit 142 may generate a signal (e.g., P). The signal OUT may be a combination of the signals IN and a signal (e.g., P).
The circuit 140 may be operational to generate a systematic convolutional rate ½ code. The circuit 142 may implement another RSC circuit, similar to circuits 104 and 106. The circuit 142 may be operational to generate a parity word p in the signal P in response to the information word d received in the signal IN.
Referring to
A signal (e.g., LIN(D)) may be received by the circuit 150 from a modulator. A signal (e.g., LIN(P)) may also be received by the circuit 150 from the modulator. Another signal (e.g., LA(D)) may be sent from the modulator to the circuit 150. The circuit 150 may generate a signal (e.g., LOUT(D)). A signal (e.g., LOUT(P)) may also be generated by the circuit 150. A signal (e.g., LE(D)) may be generated by the circuit 150.
The circuit 150 may implement a MAP decoder circuit. A part of the turbo decoding process is the MAP decoding process. The MAP decoding process may be applied for any convolutional code. In the case of rate ⅓ turbo code, the MAP decoding may be applied for systematic convolutional rate ½ codes only. In some embodiments, the circuit 150 may be operational to perform a Max-Log-MAP decoding process. Other MAP decoding processes may be implemented to meet the criteria of a particular application.
The signal LIN(D) may carry an LLR soft decision from the modulator for the information bits d. The signal LIN(P) may convey an LLR soft decision for the parity bits p. The signal LA(D) generally carries LLR soft decision a priori probability data for the information bits d. LLR soft decisions of MAP decoder (circuit 150) may be carried in the signal LOUT(D) for the information bits d and the signal LOUT(P) for the parity bits p. Extrinsic LLR data used in turbo decoding between half iterations may be presented in the signal LE(D).
Referring to
The signal LIN(D) may be received by the circuit 160 from a modulator. Multiple signals for parity (e.g., LIN(P1), LIN(P2) and LIN(P3)) may also be received by the circuit 160 from the modulator. The circuit 160 may generate a signal (e.g., D). A signal (e.g., P1) may also be generated by the circuit 160. A signal (e.g., P2) may be generated by the circuit 160. The circuit 160 may also generate a signal (e.g., P3).
The circuit 160 may implement a Viterbi decoder circuit. The circuit 160 is generally operational to decode according to the Viterbi decoding process. The Viterbi process is generally used for decoding of convolutional codes. The same hardware may be utilized for performing state metric recursions in both the Viterbi process and the MAP decoding process (e.g., circuit 150). The circuit 160 generally uses LLR soft decisions from the modulator for information bits d and parity bits p as received in the signals LIN(D), LIN(P1), LIN(P2) and LIN(P3). The result of Viterbi decoder work may be the hard decisions for the reconstructed information bits {circumflex over (d)} and the reconstructed parity bits {circumflex over (p)}. The hard decisions may be carried in the signals D, P1, P2 and P3 respectively.
Referring to
Referring to
Both the Max-Log-MAP decoding process for turbo decoding and the Viterbi decoding process for convolutional decoding may be based on the same procedure. The procedure generally computes (i) for each edge e in the code trellis a quantity γ(e) called a branch metric and (ii) for each vertex q in each level Vi of the code trellis a number of quantities called state metrics: αt(q) and βt(q) in Max-Log-MAP decoding; and αt(q) in Viterbi decoding. All the quantities may be in the domain R∪{∞}, where R may be the set of real numbers. In hardware implementations of a decoder, integer arithmetic may be used instead of real numbers.
In the case of Max-Log-MAP decoding, the computation for trellis of length n may be as illustrated in formulae 15 to 18 as follows:
where q0 may be an initial state of the encoder. In the case of Viterbi decoding, a recursion for α state metrics may be implemented. Furthermore, for each computed αt+1(q′), the edge e should be remembered such that αt(q)+γ(e) are maximal.
The branch metrics for edge e in a radix-4 Max-Log-MAP decoding for turbo codes is generally computed by formula 19 as follows:
γ(e)=(−1)x
where x1 and x2 may be information bits, and z1 and z2 may be parity bits associated with the edge e. Branch metrics calculations may include (i) a priori soft LLR values A1,A2 for information bits x1,x2 from the signal LA(D), (ii) soft LLR values X1,X2 for information bits x1,x2 from the signal LIN(D) and (iii) soft LLR values Z1,Z2 for parity bits z1,z2 from the signal LIN(P).
Branch metrics for edge e in radix-4 Viterbi decoding process for rate ⅓ convolutional code may be computed by formula 20 as follows:
Parity bits z1(i),z2(i) may be associated with the edge e and soft LLR values Z1(i),Z2(i) from the signal LIN(P) may be used (see for the case s=3). When all of the state and branch metrics are computed, the decoders generally produce soft LLR decisions in the signals LOUT(D), LOUT(P) for the information bits and the parity bits respectively and extrinsic LLR's in the signal LE(D) in the Max-Log-MAP decoding process (e.g., circuit 150) and hard decisions in the signals D, P(1), . . . , P(s) in the Viterbi decoding process (e.g., circuit 160).
Referring to
The circuit 182 may present a signal to the circuit 184a and the circuit 188a. Each circuit 184a to 184m-1 may present a signal to the next respective circuit 184b to 184m, a respective circuit 186a to 186m-1 and a respective circuit 190a to 190m-1. The circuit 184m may present a signal to the circuits 186m and 190m. Each circuit 186a to 186m may present a signal to a respective circuit 188a to 188m. Each circuit 188a to 188m-1 may present a signal to a respective next circuit 188b to 188m. Each circuit 190a to 190m-1 may present a signal to a respective circuit 192a to 192m-1. The circuit 190m may also present a signal to the circuit 192m-1. Each circuit 192b to 192m-1 may present a signal to a respective previous circuit 192a to 192m-2. The circuit 192a may present a signal back to the circuit 182.
Each circuit 182, 188a to 188m and 192a to 192m-1 may implement an adder circuit. The circuits 182, 188a to 188m and 192a to 192m-1 are generally operational to generate a sum at an output port of two values received at the respective input ports.
Each circuit 184a to 184m may implement a delay circuit (e.g., register). The circuit 184a-184m may be operational to buffer a received value for a single clock cycle.
Each circuit 186a to 186m may implement a transfer circuit. The circuit 186a to 186m may be operational to transfer an input value to an output value per a respective polynomial (e.g., A1 to Am).
Each circuit 190a to 190m may implement another transfer circuit. The circuit 190a to 190m may be operational to transfer an input value to an output value per a respective polynomial (e.g., B1 to Bm). A number of additional rates may be easily obtained by applying puncturing. Puncturing generally deletes some of the parity symbols according to a puncturing scheme defined in each standard.
Trellises of different convolutional codes generally have similar structure. The similarities may enable a reduction in the complexity of a universal trellis decoder suitable for working with many trellises. Consider a rate 1 convolutional encoder where a state transition of any rate 1/s encoder is the same. An encoder state q may be defined by formula 21 as follows:
q(t)=[q1(t), . . . , qm(t)]εF2m (21)
where x(t)εF2, and y(t)εF2 are an input and output at the moment t=0, 1, . . . . Choosing an initial state q(0) of the encoder per formula 22 as follows:
q(0)=[q1(0), . . . , qm(0)]εF2m (22)
the work of the encoder may be described by formula 23 as follows:
and in a compact form by formula 24 as follows:
A transition function may be described by formula 25 as follows:
δ:F2m×F2→F2m (25)
An output function of finite automaton that corresponds to the encoder may be given by formula 26 as follows:
λ:F2m×F2→F2 (26)
Referring to
Returning to formula 23, if bm=1, the automata may be seen as a permutation automata. In a permutation automata, each input xεF2 may permute the set of states F2. If a0=1, the formula 27 as follows:
y(t)=a0x(t)+a1q1(t)+ . . . +amqm(t) (27)
generally shows that if q(t) is fixed then y(t) is either x(t) or
q1 . . . qm-2**:={q1 . . . qm-200,q1 . . . qm-201,q1 . . . qm-210,q1 . . . qm-211} (28)
By applying a set of input words {00,01,10,11}, a set described by formula 29 may be obtained as follows:
**q1 . . . qm-2:={00q1 . . . qm-2,01q1 . . . qm-2,10q1 . . . qm-2,11q1 . . . qm-2} (29)
Moreover, the corresponding transition graph 200 may be a full bipartite graph K4,4.
Referring to
A signal (e.g., SM0) and a signal (e.g., BM0) may be received by the circuit 222a. The circuit 222b may receive a signal (e.g., SM1) and a signal (e.g., BM1). A signal (e.g., SM2) and a signal (e.g., BM2) may be received by the circuit 222c. The circuit 222d may receive a signal (e.g., SM3) and a signal (e.g., BM3). The circuit 224 may receive the sums from the circuits 222a to 222d. A signal (e.g., IND) may be generated by the circuit 224. The circuit 224 may also generate a signal (e.g., SM).
As may be seen from the formulae for the state metrics (α and β) computations in the Max-Log-MAP decoding and the Viterbi decoding, a common operation used is a maximum of a number of sums. In the case of a radix-4 trellis, the maximum number may be 4. In hardware, the computations may be performed in an add-compare-select circuit (e.g., circuit 220).
The circuits 222a to 222d may implement adder circuits. Each circuit 222a to 222d may be operational to add a branch metric value and a respective state metric value. The sums may be the “add” portion of the add-compare-select operations.
The circuit 224 may implement a compare and select circuit. The circuit 224 is generally operational to compare the sum values calculated by the circuits 222a to 222d. The circuit 224 may also be operational to select a maximum sum value from among the sum values. The selected maximum sum value may be presented in the signal SM as a new state metric value. The new state metric value may be computed per formula 30 as follows:
An index value iε{0, . . . , 3} of the selected maximum sum value may be presented in the signal IND.
Referring to
Consider a convolutional code with 256 states. A transition graph (e.g., transition graph 200) generally has 64 K4,4 components and each component may be processed in parallel in the Viterbi decoding. In the case of turbo codes, subgraphs generally cannot be process in parallel because the state metrics are calculated in each clock cycle. Therefore, the universal dependence graph 230 may be implemented according to the encoder state transition graph (e.g., transition graph 200). By way of example, the graph 230 generally illustrates transitions to the state 110 (e.g., having a zero last bit) from the states 000, 001, 010, 011 (e.g., each having a zero initial bit).
To construct a state metrics calculation circuit, each vertex of the dependent graph 230 may be associated with the circuit 220. The circuits 220 may be inter-connected according to the transitions of the dependent graph 230 to obtain a state metric calculator (SMC) for radix-4 trellis decoding. Each vertex of the dependent graph 230 generally has incoming transitions of degree 4.
Consider a high-speed turbo decoder that calculates state metrics for vertexes in a level Vt of the trellis in parallel in single clock cycle. The state metrics obtained for the level Vt may be used on the next clock cycle for computations of state metrics in next level Vt+1. Therefore, the SMC generally cannot be pipelined. For encoders used in different communications standards, different trellises may be used and so multiplexers may be implemented at the input ports of the ACS circuits in some designs. However, the dependence graphs for several communications standards, such as W-CDMA, LTE, CDMA2000 and WiMAX, may be isomorphic to the dependence graph 230 shown in
Referring to
The circuit 242a may receive a signal (e.g., X1) and a signal (e.g., A1). The circuit 242b may receive a signal (e.g., X2) and a signal (e.g., A2). A signal (e.g., Z1) may be received by the circuit 244b. A signal (e.g., Z2) may also be received by the circuit 244b. A sum of the signals X1 and A1 may be presented from the circuit 242a to the circuit 244a. A sum of the signals X2 and A2 may be presented from the circuit 242b to the circuit 244a. The circuit 244a may generate a sum value that is presented to the circuits 246a to 246d. The circuit 244b may generate a sum value that is presented to the circuits 246e to 246h. A signal (e.g., CONF) may be received by each circuit 246a to 246h. Each circuit 248a to 248h may receive a permuted value from different pairs of the circuits 246a to 246h. A signal (e.g., BM) may be created by a combination of the sum values generated by the circuits 248a to 248h.
The signals X1, X2 may convey soft LLR values for the information bits x1,x2. The signals A1,A2 may carry a priori soft LLR values for the information bits x1,x2. The signals Z1,Z2 may carry soft LLR values for the parity bits z1,z2. By way of example, each soft value may have a bit-width of w. The signal CONF may carry configuration information that identifies a particular communications standard from among several communications standards that the circuit 240 may process.
Each circuit 242a to 242b may implement an adder circuit. The circuits 242a to 242b may be operational to add the soft LLR values received in the respective signals X1,A1 and X2,A2 to calculate a sum value.
Each circuit 244a to 244b may implement a universal sum circuit. The circuits 244a to 244b are generally operational to calculate several (e.g., 4) output values (e.g., Y00, Y01, Y10, Y11) from multiple (e.g., 2) input values (e.g., R0, R1). The output values may be calculated according to formula 31 as follows:
Yx
where x0x1ε{00,01,10,11}.
Each circuit 246a to 246h may implement a universal switch (USW) circuit. The circuits 246a to 246h may by operational to permute the output values received from the circuits 244a to 244b to generate the permuted values presented to the circuits 248a to 248h. Control of the permutations may be provided through the signal CONF. The signal CONF generally comprises multiple control bits (e.g., a different set of bits σ, σ0, σ1 for each circuit 246a to 246h). Each permutation generally corresponds to the permutation that performs on set {00,01,10,11} finite state automaton.
Referring to
Returning to
Each circuit 248a to 248h may implement an adder circuit. The circuits 248a to 248h are generally operational to add the permuted values received from the circuits 246a to 246h to generate the branch metrics values. The branch metrics value may be calculated according to formula 32 as follows:
BMij=XSWij+ZSWij, i=0, . . . , 7; j=0, . . . , 3 (32)
in which BMij may be a branch metric that corresponds to the j-th clockwise edge from i-th state (in binary representation A2A1A0) on the dependence graph 230 A combination of the individual branch metrics values may be presented in the signal BM.
The circuit 240 may be pipelined. For example, an initial pipeline stage may be created with the circuits 242a, 242b, 244a and 244b. A next pipeline stage may be formed with the circuits 246a to 246h and 248a to 248h. Other pipeline arrangements may be implemented to meet the criteria of a particular application. Therefore, the circuit 240 generally does not restrict a performance of the decoder.
Referring to
The circuit 282 may receive the values Y00 and Y01 from the circuit 244a and the value σ0 from the signal CONF. The values Y10 and Y11 may be received by the circuit 284 from the circuit 244a and the value σ1 from the signal CONF. The circuit 286 may receive the permuted values from the circuits 282 and 284. The circuit 286 may also receive the value σ from the signal CONF. Permuted signals (e.g., Y′00, Y′01, Y′10 and Y′11) may be generated by the circuit 286 and presented to the circuits 248a to 248h.
Each circuit 282, 284 and 286 may implement a multiplexer circuit. The circuit 282 may be operational to permute the values Y00 and Y01 in response to the value σ0. While the value σ0 is a logical 1, the values Y00 and Y01 may be passed straight through. While the value σ0 is a logical 0, the values Y00 and Y01 may be exchanged. The circuit 284 may be operational to permute the values Y10 and Y11 in response to the value σ1. While the value of is a logical 1, the values Y10 and Y11 may be passed straight through. While the value σ1 is a logical 0, the values Y10 and Y11 may be exchanged. The circuit 286 may be operational to permute the values received from the circuits 282 and 284 in response to the value σ. While the value σ is a logical 1, (i) the values received from the circuit 282 may be passed straight through as the values Y′00 and Y′01 and (ii) the values received from the circuit 284 may be passed straight through as the values Y′10 and Y′11. While the value σ is a logical 0, the two values received from the circuit 282 may be exchanged with the two values received from the circuit 284. The resulting permutation for each value Y00, Y01, Y10 and Y11 is generally illustrated by the state transition diagram 260.
Some embodiments of the present invention may implement a configurable BMC circuit instead of implementing multiplexers at the input ports of the ACS circuit. The configurable BMC circuit generally supports multiple communications standards. An ordinary way to support multiple standards in single decoder is to implement multiplexers in a SMC circuit along a main path through the decoder. By using the configurable BMC circuit, the main path through the SMC circuit may be free from the multiplexers. Furthermore, the universal switch circuits used in the BMC circuit generally occupy a low silicon area, but at the same time may support any permutations of branch metrics arising in various wired and/or wireless communications standards.
The functions performed by the diagrams of
The present invention may also be implemented by the preparation of ASICs (application specific integrated circuits), Platform ASICs, FPGAs (field programmable gate arrays), PLDs (programmable logic devices), CPLDs (complex programmable logic device), sea-of-gates, RFICs (radio frequency integrated circuits), ASSPs (application specific standard products), one or more monolithic integrated circuits, one or more chips or die arranged as flip-chip modules and/or multi-chip modules or by interconnecting an appropriate network of conventional component circuits, as is described herein, modifications of which will be readily apparent to those skilled in the art(s).
The elements of the invention may form part or all of one or more devices, units, components, systems, machines and/or apparatuses. The devices may include, but are not limited to, servers, workstations, storage array controllers, storage systems, personal computers, laptop computers, notebook computers, palm computers, personal digital assistants, portable electronic devices, battery powered devices, set-top boxes, encoders, decoders, transcoders, compressors, decompressors, pre-processors, post-processors, transmitters, receivers, transceivers, cipher circuits, cellular telephones, digital cameras, positioning and/or navigation systems, medical equipment, heads-up displays, wireless devices, audio recording, storage and/or playback devices, video recording, storage and/or playback devices, game platforms, peripherals and/or multi-chip modules. Those skilled in the relevant art(s) would understand that the elements of the invention may be implemented in other types of devices to meet the criteria of a particular application.
As would be apparent to those skilled in the relevant art(s), the signals illustrated in
While the invention has been particularly shown and described with reference to the preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made without departing from the scope of the invention.
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