Optimization of signal sets for partial-response channels. I. Numerical techniques

Honig, Michael L.; Steiglitz, K.; Norman, Stephen A.

doi:10.1109/18.133250

Cited by 11 publications

(2 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this case, H(f) = G ( f ) H , ( f ) , and the problem is to jointly select the channel inputs as well as the channel transfer function to maximize the minimum distance d2 given by (1).…”

Section: A Channel Shaping Problemsmentioning

confidence: 99%

Channel shaping to maximize minimum distance

Honig¹

1993

IEEE Trans. Inform. Theory

Self Cite

View full text Add to dashboard Cite

Suppose that N inputs to a linear, time-invariant channel are designed to maximize the minimum L , distance between channel outputs. It is assumed that all inputs are zero outside the finite time window [-T , TI and are constrained in energy. The jointly optimal inputs and channel frequency response H(f) for which the minimum distance is maximized is studied, subject to the constraint that the L , norm of H(f) is bounded. This leads to an ellipse packing problem in which N-1 axis lengths, which define an ellipse in RN-', and N points inside the ellipse are to be chosen to maximize the minimum Euclidean distance between points, subject to the constraint that the sum of the squared axis lengths is constant. An optimality condition is derived, and it is conjectured that the optimal ellipse in which the N points must lie is an n-dimensional sphere, where n I N. An approximate volume calculation suggests that n increases as O(log N). As T + x , this implies that an optimal channel response is ideal bandlimited with bandwidth 2R' Hz, where R' = (log, N) / (Z T) is the information rate.

show abstract

“…In this case, H(f) = G ( f ) H , ( f ) , and the problem is to jointly select the channel inputs as well as the channel transfer function to maximize the minimum distance d2 given by (1).…”

Section: A Channel Shaping Problemsmentioning

confidence: 99%

Channel shaping to maximize minimum distance

Honig¹

1993

IEEE Trans. Inform. Theory

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the area of signal design we note the work of Honig et al [11] where optimum signal sets for dispersive channels are derived in a framework based on channel eigen-decomposition [10]. We also note the work of Kasturia et al [13] and Lechleider [14] that propose codeword design methods for block transmissions suited for multicarrier modulation systems.…”

Section: Introductionmentioning

confidence: 99%

Codeword optimization for uplink CDMA dispersive channels

Popescu

Rose

2005

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

Abstract-We present the application of greedy interference avoidance methods to codeword optimization in the uplink of a code division multiple access (CDMA) system in which the channel between a given user and the base station receiver is assumed known and stable for the duration of the transmission. Repeated application of greedy interference avoidance monotonically increases sum capacity and yields an optimal codeword ensemble that satisfies a simultaneous water-filling distribution. However, algorithms for codeword optimization based on the greedy interference avoidance procedure are in general different from waterfilling schemes. We illustrate the algorithms with examples and look at properties of optimal codeword ensembles.Index Terms-CDMA, codeword adaptation, distributed interference avoidance, sum capacity optimization.

show abstract

Shaping the boundary of a multi-dimensional signal constellation with a non-flat power spectrum

Khandani

1998

IEE Proc., Commun.

View full text Add to dashboard Cite

Optimization of signal sets for partial-response channels. I. Numerical techniques

Cited by 11 publications

References 26 publications

Channel shaping to maximize minimum distance

Channel shaping to maximize minimum distance

Codeword optimization for uplink CDMA dispersive channels

Shaping the boundary of a multi-dimensional signal constellation with a non-flat power spectrum

Contact Info

Product

Resources

About