Loading [MathJax]/extensions/MathMenu.js
Design of Signature Sequences for Overloaded CDMA and Bounds on the Sum Capacity With Arbitrary Symbol Alphabets | IEEE Journals & Magazine | IEEE Xplore

Design of Signature Sequences for Overloaded CDMA and Bounds on the Sum Capacity With Arbitrary Symbol Alphabets


Abstract:

In this paper, we explore some of the fundamentals of synchronous Code Division Multiple Access (CDMA) as applied to wireless and optical communication systems under very...Show More

Abstract:

In this paper, we explore some of the fundamentals of synchronous Code Division Multiple Access (CDMA) as applied to wireless and optical communication systems under very general settings (of any size) for the user symbols and the signature matrix entries. The channel is modeled by real/complex additive noise of arbitrary distribution. Two problems are addressed. The first problem concerns whether uniquely detectable overloaded matrices exist in the absence of additive noise under these general settings, and if so, whether there are any practical optimum detection algorithms. The second one is about the bounds for the sum channel capacity when user data and signature matrices employ any real or complex alphabets (finite or infinite). In response to the first problem, we have developed practical maximum likelihood detection algorithms for overloaded CDMA systems for a large class of alphabets. In response to the second problem, a general theorem has been developed in which the sum capacity lower bounds with respect to the number of users, spreading gain, and signal-to-noise ratio can be derived. To show the power and utility of the main theorem, a number of sum capacity bounds for special cases are evaluated. An important conclusion of this paper is that the lower and upper bounds of the sum capacity for small/medium-size CDMA systems depend on both the input and the signature symbols; this is contrary to the asymptotic results for large-scale systems reported in the literature (also confirmed in this paper) where the signature symbols and statistics disappear for signature matrices and input vectors with i.i.d. entries. Furthermore, upper and asymptotic bounds are derived and compared to other derivations.
Published in: IEEE Transactions on Information Theory ( Volume: 58, Issue: 3, March 2012)
Page(s): 1441 - 1469
Date of Publication: 18 October 2011

ISSN Information:

References is not available for this document.

A. Introduction

Code Division Multiple Access (CDMA) is an alternative to frequency and time division multiple access (FDMA and TDMA). CDMA has become the standard for the Universal Mobile Telecommunication Systems (UMTS) and American cellular systems [1]. Also, optical CDMA systems have become an alternative multiple access for fiber optics and optical wireless systems [2]–[4]. The reasons, to name a few, are its simplicity, high loading factor,

The number of users divided by the spreading gain .

and soft hand-off. In this paper, we will discuss some open issues related to uncoded synchronous CDMA systems of any size with finite input alphabet and matrix elements from arbitrary given alphabet (finite or infinite). The channel is modeled with real/complex additive noise with arbitrary distribution.

Select All
1.
T. Ojanpera and R. Prasad, Wideband CDMA for Third Generation Mobile Communications: Universal Personal Communications, MA, Norwood:Addison-Wesley, 1998.
2.
F. R. K. Chung, J. A. Salehi and V. K. Wei, "Optical orthogonal codes: Designanalysis and applications", IEEE Trans. Inf. Theory, vol. 35, no. 3, pp. 595-604, May 1989.
3.
S. Mashhadi and J. A. Salehi, "Code-division multiple-accesstechniques in optical fiber networks part III: Optical AND gate receiver structurewith generalized optical orthogonal codes", IEEE Trans. Commun., vol. 54, no. 6, pp. 1349-1349, Jul. 2006.
4.
J. A. Salehi, "Emerging OCDMA communicationsystems and data networks", J. Opt. Network., vol. 6, no. 9, pp. 1138-1178, Sept. 2007.
5.
S. Verdu, Multiuser Detection, New York:Cambridge Univ. Press, 1998.
6.
A. J. Viterbi, CDMA: Principles of Spread Spectrum Communication, New York:Addison-Wesley, 1995.
7.
J. L. Massey and T. Mittelholzer, "Welchs bound and sequence sets for code-division multiple-access systems" in Sequences II Methods in Communication Security and Computer Sciences, New York:Springer-Verlag, 1993.
8.
M. Rupf and J. L. Massey, "Optimum sequences multisetsfor synchronous code-division multiple-access channels", IEEE Trans. Inf. Theory, vol. 40, no. 4, pp. 1261-1266, Jul. 1994.
9.
L. Welch, "Lower bound on the maximumcross correlation of signals", IEEE Trans. Inf. Theory, vol. 20, no. 3, pp. 397-399, May 1974.
10.
T. Tanaka, "A statistical-mechanics approachto large-system analysis of CDMA multiuser detectors", IEEE Trans. Inf. Theory, vol. 48, no. 11, pp. 2888-2910, Nov. 2002.
11.
A. Montanari and D. N. C. Tse, "Analysis of belief propagationfor non-linear problems: The example of CDMA (or: How to prove Tanakas formula)", Proc. IEEE Inf. Theory Workshop, pp. 160-164, 2006-Mar.
12.
D. Guo and S. Verdu, "Randomly spread CDMA: Asymptotics via statisticalphysics", IEEE Trans. Inf. Theory, vol. 51, no. 6, pp. 1983-2010, Mar. 2005.
13.
S. B. Korada and N. Macris, "On the concentration of thecapacity for a code division multiple access system", Proc. IEEE Int. Symp. Inf. Theory, pp. 2801-2805, 2007-June.
14.
S. B. Korada and N. Macris, "Tight bounds on the capacityof binary input random CDMA systems", IEEE Trans. Inf. Theory, vol. 56, no. 11, pp. 5590-5613, Nov. 2010.
15.
O. Shental, I. Kanter and A. Weiss, "Capacity of complexity-constrained noise-freeCDMA", IEEE Commun. Lett., vol. 10, no. 1, pp. 10-12, Jan. 2006.
16.
R. de Miguel, O. Shental and R. Muller, "Information and multiaccessinterference in a complexity-constrained vector channel", J. Physics A Math. Th., vol. 40, no. 20, pp. 5241-5260, 2007.
17.
P. Pad, F. Marvasti, K. Alishahi and S. Akbari, "A class of errorless codesfor over-loaded synchronous wireless and optical CDMA systems", IEEE Trans. Inf. Theory, vol. 55, no. 6, pp. 2705-2715, Jun. 2009.
18.
K. Alishahi, F. Marvasti, V. Aref and P. Pad, "Bounds on the sum capacity of synchronous binary CDMA channels", IEEE Trans. Inf. Theory, vol. 55, no. 8, pp. 3577-3593, Aug. 2009.
19.
D. Guo and C. C. Wang, "Multiuser detection of sparselyspread CDMA", IEEE J. Sel. Areas Commun., vol. 26, no. 3, pp. 421-431, Apr. 2008.
20.
W. H. Mow, "Recursive constructions ofdetecting matrices for multiuser coding: A unifying approach", IEEE Trans. Inf. Theory, vol. 55, no. 1, pp. 93-98, Jan. 2009.
21.
P. Pad, M. Soltanolkotabi, S. Hadikhanlou, A. Enayati and F. Marvasti, "Errorless codes for over-loaded CDMA withactive user detection", ICC09, 2009-Jun.
22.
S. Sderberg and H. S. Shapiro, "A combinatory detection problem", Amer. Math. Monthly, vol. 70, no. 10, pp. 1066-1070, Dec. 1963.
23.
R. Erds and A. Rnyi, "On two problems of informationtheory", Magyar Tud. Akad. Mat. Kutato Int. Ko zl., vol. 8A, pp. 229-243, 1963.
24.
B. Lindstrm, "On a combinatory detectionproblem", Publ. Hung. Acad. Sci., vol. 9, pp. 195-207, 1964.
25.
D. G. Cantor and W. H. Mills, "Determining a subset from certaincombinatorial properties", Can. J. Math., vol. 18, pp. 42-48, 1966.
26.
B. Lindstrm and J. N. Srivastava, "Determining subsets by unramified experiments" in A Survey of Statistical Design and Linear Models, New York:North-Holland, 1975.
27.
S. S. Martirossian and G. H. Khachatrian, "Construction of signature codesand the coin weighing problem", Probl. Inf. Trans., vol. 25, pp. 334-335, Oct.Dec. 1989.
28.
B. Lindstrm, "On mbius functions anda problem in combinatorial number theory", Can. Math. Bull., vol. 14, pp. 513-516, 1971.
29.
G. H. Khachatrian and S. S. Martirossian, "Codes for T-user noiselessadder channel", Probl. Control Inf. Theory, vol. 16, no. 3, pp. 187-192, 1987.
30.
M. H. Shafinia, P. Kabir, P. Pad, S. M. Mansouri and F. Marvasti, "Errorless codes for CDMA system with near-far effect", ICC2010, 2010-May.
Contact IEEE to Subscribe

References

References is not available for this document.