Add to ORKGAbstract—For the additive white Gaussian noise channel with average codeword power constraint, new coding methods are devised in which the codewords are sparse superpositions, that is, linear combinations of subsets of vectors from a given design, with the possible messages indexed by the choice of subset. Decoding is by least squares, tailored to the assumed form of linear combination. Communication is shown to be reliable with error probability exponentially small for all rates up to the Shannon capacity. I
Sparse superposition (SS) codes were originally proposed as a capacity-achieving communication schem...
We study a new class of codes for lossy compression with the squared-error distortion crite-rion, de...
Abstract The recently proposed superposition codes (SCs) have been mathematically proved to be decod...
Abstract—For the additive Gaussian noise channel with aver-age codeword power constraint, sparse sup...
Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication ...
Abstract—For the additive white Gaussian noise channel with average codeword power constraint, spars...
Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication ...
Sparse superposition codes, or sparse regression codes, constitute a new class of codes, which was f...
A method for power- and bandwidth efficient communication over the Gaussian channel is presented. Th...
We study a new class of codes for lossy compression with the squared-error distortion criterion, des...
Sparse superposition codes were originally proposed as a capacity-achieving communication scheme ove...
Sparse superposition codes, also referred to as sparse regression codes (SPARCs), are a class of cod...
Abstract—Superposition codes are efficient for the Additive White Gaussian Noise channel. We provide...
Sparse superposition codes, or sparse regression codes (SPARCs), are a recent class of codes for rel...
Abstract—We study a new class of codes for Gaussian multi-terminal source and channel coding. These ...
Sparse superposition (SS) codes were originally proposed as a capacity-achieving communication schem...
We study a new class of codes for lossy compression with the squared-error distortion crite-rion, de...
Abstract The recently proposed superposition codes (SCs) have been mathematically proved to be decod...
Abstract—For the additive Gaussian noise channel with aver-age codeword power constraint, sparse sup...
Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication ...
Abstract—For the additive white Gaussian noise channel with average codeword power constraint, spars...
Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication ...
Sparse superposition codes, or sparse regression codes, constitute a new class of codes, which was f...
A method for power- and bandwidth efficient communication over the Gaussian channel is presented. Th...
We study a new class of codes for lossy compression with the squared-error distortion criterion, des...
Sparse superposition codes were originally proposed as a capacity-achieving communication scheme ove...
Sparse superposition codes, also referred to as sparse regression codes (SPARCs), are a class of cod...
Abstract—Superposition codes are efficient for the Additive White Gaussian Noise channel. We provide...
Sparse superposition codes, or sparse regression codes (SPARCs), are a recent class of codes for rel...
Abstract—We study a new class of codes for Gaussian multi-terminal source and channel coding. These ...
Sparse superposition (SS) codes were originally proposed as a capacity-achieving communication schem...
We study a new class of codes for lossy compression with the squared-error distortion crite-rion, de...
Abstract The recently proposed superposition codes (SCs) have been mathematically proved to be decod...