Nguyen Van Phe – Post-graduate Student, Higher School of Applied Physics and Space Technologies, 

Peter The Great St. Petersburg Polytechnic University

E-mail: nvphe1905@gmail.com

A.I. Gorlov – Ph.D.(Eng.), Assistant, Higher School of Applied Physics and Space Technologies, 

Peter The Great St. Petersburg Polytechnic University

E-mail: anton.gorlov@yandex.ru

A.L. Gelgor – Ph.D.(Eng.), Associate Professor, Higher School of Applied Physics and Space Technologies, 

Peter The Great St. Petersburg Polytechnic University

E-mail: a_gelgor@mail.ru

This paper explores a possibility to increase bandwidth efficiency of signals with controlled inter symbol interference (ISI) by increasing signal constellation size. We investigate single carrier signals with QPSK and 16-QAM signal constellations for this purpose. The controlled ISI is introduced by using the optimal finite pulses, which obtained by the linear optimization. The criterion of the optimization problem was maximization of the free Euclidean distance for chosen signal constellation under a fixed bandwidth comprising 99% of signal power. The single carrier channel with additive white Gaussian noise was used in simulation model. We used the sphere decoding for signals detection. The simulation results have shown that the maximal bandwidth efficiency is achieved only by simultaneous increasing of the signal constellation size and introducing of the controlled ISI.

1. Mazo J.E. Faster-than-Nyquist signaling // Bell System Technical Journal. 1975. V. 54. № 8. P. 1451−1462.
2. Rusek F., Anderson J.B. Constrained Capacities for Faster-Than-Nyquist Signaling // IEEE Trans. Inf. Theory. February 2009. V. 55. № 2. P. 764−775.
3. Rusek F., Anderson J.B. The Two Dimensional Mazo Limit // Proceedings of International Symposium on Inf. Theory. 2005. P. 970−974.
4. Kanaras A. Chorti, Rodrigues M.R.D. ,Darwazeh I. Spectrally efficient FDM signals: bandwidth gain at the expense of receiver complexity // IEEE International Conference on Communications ICC. 2009. P. 1−6.
5. Liveris D., Georghiades C.N. Exploiting faster-than-Nyquist signaling // IEEE Trans. Comm. 2003. V. 51. № 9. P. 1502−1511.
6. Gel'gor A.L., Gorlov A.I., Nguen Van Fe. Povy'shenie e'ffektivnosti SEFDM putem zameny' spektral'ny'x sinc-impul'sov na RRC-impul'sy' // Radiotexnika. 2016. № 12. S. 105−111.
7. Said, Anderson J.B. Bandwidth-efficient coded modulation with optimized linear partial-response signals // IEEE Trans. Inform. Theory. 1998. V. 44. № 2. P. 701−713.
8. Gel'gor A.L., Gorlov A.I., Popov E.A. Preodolenie «bar'era» Najkvista pri ispol'zovanii odnochastotny'x neortogonal'ny'x mnogokomponentny'x signalov // Radiotexnika. 2015. № 1. S. 32−48.
9. Forney G.D. The Viterbi Algorithm // Proc. of the IEEE. 1973. V. 61. № 3. P. 268−278.
10. Bahl L., Cocke J., Jelinek F., Raviv J. Optimal decoding of linear codes for minimizing symbol error rate // IEEE Trans. Inf. Theory. 1974. V. 20. № 2. P. 284−287.
11. Fincke U., Pohst M. Improved Methods for Calculating Vectors of Short Length in a Lattice, Including a Complexity Analysis // Mathematics of computation. 1985. V. 44. № 170. P. 463−471.
12. Wang P., T. Le-Ngoc. On the expected complexity analysis of a generalized sphere decoding algorithm for underdetermined linear communication systems // Proc. IEEE ICC. Glasgow (Scotland). June 2007.
13. G.H. Li, Zhang X., Lei S., Xiong C., Yang D.C. An early termination-based improved algorithm for fixed-complexity sphere decoder // Proc. IEEE WCNC. April 2012. Paris (France).
14. Babak Hassibi, Haris Vikalo. On the Sphere-Decoding Algorithm I. Expected Complexity // IEEE Trans. sig. proc. 2005. V. 53. № 8.
15. Shim B., Kang I. On further reduction of complexity in tree pruning based sphere search // IEEE Trans. Commun. Febraury 2010. V. 58. № 2. P. 417−422.
16. Junil Ahn, Heung-no Lee, Kiseon Kim. Expected complexity analysis of increasing radii algorithm by considering multiple radius schedules // IET Communications. 2013. V. 7. № 3. P. 229−235.