Elements of information theory
Elements of information theory
Multiuser Detection
A class of errorless codes for overloaded synchronous wireless and optical CDMA systems
IEEE Transactions on Information Theory
Spectral efficiency of CDMA with random spreading
IEEE Transactions on Information Theory
Optimal sequences and sum capacity of synchronous CDMA systems
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Optimum asymptotic multiuser efficiency of randomly spread CDMA
IEEE Transactions on Information Theory
Binomial and Poisson distributions as maximum entropy distributions
IEEE Transactions on Information Theory
A statistical-mechanics approach to large-system analysis of CDMA multiuser detectors
IEEE Transactions on Information Theory
How much training is needed in multiple-antenna wireless links?
IEEE Transactions on Information Theory
Randomly spread CDMA: asymptotics via statistical physics
IEEE Transactions on Information Theory
Maximizing the entropy of a sum of independent bounded random variables
IEEE Transactions on Information Theory
Constructing and decoding GWBE codes using Kronecker products
IEEE Communications Letters
Hi-index | 754.84 |
In this paper, we obtain a family of lower bounds for the sum capacity of code-division multiple-access (CDMA) channels assuming binary inputs and binary signature codes in the presence of additive noise with an arbitrary distribution. The envelope of this family gives a relatively tight lower bound in terms of the number of users spreading gain, and the noise distribution. The derivation methods for the noiseless and the noisy channels are different but when the noise variance goes to zero, the noisy channel bound approaches the noiseless case. The behavior of the lower bound shows thut for small noise power, the number of users can be much more than the spreading gain without any significant loss of information (overloaded CDMA). A conjectured upper bound is also derived under the usual assumption that the users send out equally likely binary bits in the presence of additive noise with an arbitrary distribution. As the noise level increases, and/or, the ratio of the number of users and the spreading gain increases, the conjectured upper bound approaches the lower bound. We have also derived asymptotic limits of our bounds that can be compared to a formula that Tanaka obtained using techniques from statistical physics; his bound is close to that of our conjectured upper bound for large scale systems.