Evaluation of overlay/underlay waveform via sd-smse framework for enhancing spectrum efficiency

Recent studies have suggested that spectrum congestion is mainly due to the inefficient use of spectrum rather than its unavailability. Dynamic Spectrum Access (DSA) and Cognitive Radio (CR) are two terminologies which are used in the context of improved spectrum efficiency and usage. The DSA concept has been around for quite some time while the advent of CR has created a paradigm shift in wireless communications and instigated a change in FCC policy towards spectrum regulations. DSA can be broadly categorized as using a (1) Dynamic Exclusive Use Model, (2) Spectrum Commons or Open sharing model or (3) Hierarchical Access model. The hierarchical access model envisions primary licensed bands, to be opened up for secondary users, while inducing a minimum acceptable interference to primary users. Spectrum overlay and spectrum underlay technologies fall within the hierarchical model, and allow primary and secondary users to coexist while improving spectrum efficiency. Spectrum overlay in conjunction with the present CR model considers only the unused (white) spectral regions while in spectrum underlay the underused (gray) spectral regions are utilized. The underlay approach is similar to ultra wide band (UWB) and spread spectrum (SS) techniques utilize much wider spectrum and operate below the noise floor of primary users. Software defined radio (SDR) is considered a key CR enabling technology. Spectrally modulated, spectrally encoded (SMSE) multi-carrier signals such as Orthogonal Frequency Domain Multiplexing (OFDM) and Multi-carrier Code Division Multiple Access (MCCDMA) are hailed as candidate CR waveforms. The SMSE structure supports and is well-suited for SDR based CR applications. This work began by developing a general soft decision (SD) CR framework, based on a previously developed SMSE framework that combines benefits of both the overlay and underlay techniques to improve spectrum efficiency and maximizing the channel capacity. The resultant SD-SMSE framework provides a user with considerable flexibility to choose overlay, underlay or hybrid overlay/underlay waveform depending on the scenario, situation or need. Overlay/Underlay SD-SMSE framework flexibility is demonstrated by applying it to a family of SMSE modulated signals such as OFDM, MCCDMA, Carrier Interferometry (CI) MCCDMA and Transform Domain Communication System (TDCS). Based on simulation results, a performance analysis of Overlay, Underlay and hybrid Overlay/Underlay waveforms is presented. Finally, the benefits of combining overlay/underlay techniques to improve spectrum efficiency and maximize channel capacity is addressed.

[1]  Daiheng Ni,et al.  Forty-Fifth Annual Allerton Conference on Communication, Control, and Computing , 2007 .

[2]  William A. Arbaugh,et al.  Measuring Interference Temperature , 2006 .

[3]  Joseph Mitola,et al.  Cognitive Radio An Integrated Agent Architecture for Software Defined Radio , 2000 .

[4]  Shuangqing Wei,et al.  Soft-decision cognitive radio power control based on intelligent spectrum sensing , 2007, 2007 International Waveform Diversity and Design Conference.

[5]  Yiyan Wu,et al.  COFDM: an overview , 1995, IEEE Trans. Broadcast..

[6]  Vasu Chakravarthy,et al.  A transform domain communication and jamming waveform , 2006, 2006 International Waveform Diversity & Design Conference.

[7]  Robert F. Mills,et al.  A general analytic framework for spectrally modulated, spectrally encoded signals , 2006, 2006 International Waveform Diversity & Design Conference.

[8]  L. Milstein,et al.  An Analysis of a Real-Time Transform Domain Filtering Digital Communication System - Part I: Narrow-Band Interference Rejection , 1980, IEEE Transactions on Communications.

[9]  William A. Arbaugh,et al.  Dynamic spectrum access in cognitive radio networks , 2006 .

[10]  Robert F. Mills,et al.  Interference avoidance in spectrally encoded multiple access communications using MPSK modulation , 2005, IEEE Wireless Communications and Networking Conference, 2005.

[11]  Zhiqiang Wu,et al.  Interference Tolerant Agile Cognitive Radio: Maximize Channel Capacity of Cognitive Radio , 2007, 2007 4th IEEE Consumer Communications and Networking Conference.

[12]  Balasubramaniam Natarajan,et al.  High-performance MC-CDMA via carrier interferometry codes , 2001, IEEE Trans. Veh. Technol..

[13]  Lang Tong,et al.  A Measurement-Based Model for Dynamic Spectrum Access in WLAN Channels , 2006, MILCOM 2006 - 2006 IEEE Military Communications conference.

[14]  Apurva N. Mody,et al.  IEEE Standards Supporting Cognitive Radio and Networks, Dynamic Spectrum Access, and Coexistence , 2008, IEEE Communications Magazine.

[15]  S. Weinstein,et al.  Data Transmission by Frequency-Division Multiplexing Using the Discrete Fourier Transform , 1971 .

[16]  C. Cordeiro,et al.  Spectrum agile radios: utilization and sensing architectures , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[17]  P. J. Swackhammer,et al.  Performance simulation of a transform domain communication system for multiple access applications , 1999, MILCOM 1999. IEEE Military Communications. Conference Proceedings (Cat. No.99CH36341).

[18]  Dipankar Raychaudhuri,et al.  Reactive cognitive radio algorithms for co-existence between IEEE 802.11b and 802.16a networks , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[19]  S. Srinivasa,et al.  The Throughput Potential of Cognitive Radio: A Theoretical Perspective , 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.

[20]  J.D. Poston,et al.  Discontiguous OFDM considerations for dynamic spectrum access in idle TV channels , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[21]  Balasubramaniam Natarajan,et al.  Enabling FCC's proposed spectral policy via carrier interferometry , 2004, 2004 IEEE Wireless Communications and Networking Conference (IEEE Cat. No.04TH8733).

[22]  Huseyin Arslan,et al.  Cognitive radio, software defined radio, and adaptiv wireless systems , 2007 .

[23]  Pil Lee.  Computation of the Bit Error Rate of Coherent M-ary PSK with Gray Code Bit Mapping , 1986, IEEE Trans. Commun..

[24]  Americo Brajal,et al.  Orthogonal multicarrier techniques applied to direct sequence spread spectrum CDMA systems , 1993, Proceedings of GLOBECOM '93. IEEE Global Telecommunications Conference.

[25]  R.W. Brodersen,et al.  Implementation issues in spectrum sensing for cognitive radios , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[26]  Michael B. Pursley,et al.  Low-Complexity Adaptive Transmission for Cognitive Radios in Dynamic Spectrum Access Networks , 2008, IEEE Journal on Selected Areas in Communications.

[27]  Gareth Ennis,et al.  Impact of Bluetooth on 802.11 Direct Sequence , 1998 .

[28]  Alexander M. Wyglinski.  Effects of Bit Allocation on Non-Contiguous Multicarrier-Based Cognitive Radio Transceivers , 2006, IEEE Vehicular Technology Conference.

[29]  Linda Doyle,et al.  Cyclostationary Signatures in Practical Cognitive Radio Applications , 2008, IEEE Journal on Selected Areas in Communications.

[30]  John W. Betz,et al.  Detection of weak random signals in IID non-Gaussian noise , 2000, IEEE Trans. Commun..

[31]  A. Shaw,et al.  A general overlay/underlay analytic expression representing cognitive radio waveform , 2007, 2007 International Waveform Diversity and Design Conference.

[32]  Balasubramaniam Natarajan,et al.  Large set of CI spreading codes for high-capacity MC-CDMA , 2004, IEEE Transactions on Communications.

[33]  Lajos Hanzo,et al.  OFDM and MC-CDMA for Broadband Multi-User Communications, WLANs and Broadcasting , 2003 .

[34]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[35]  Wei Su,et al.  Modulation Recognition In Fading Channels Using Higher Order Cyclic Cumulants , 2007, 2007 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[36]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[37]  Apurva N. Mody,et al.  Recent advances in cognitive communications , 2007, IEEE Communications Magazine.

[38]  William A. Gardner,et al.  Spectral Correlation of Modulated Signals: Part II - Digital Modulation , 1987, IEEE Transactions on Communications.

[39]  Chia-han Lee,et al.  Multiple Access-Inspired Cooperative Spectrum Sensing for Cognitive Radio , 2007, MILCOM 2007 - IEEE Military Communications Conference.

[40]  André B. J. Kokkeler,et al.  An Efficient FFT For OFDM Based Cognitive Radio On A Reconfigurable Architecture , 2007, 2007 IEEE International Conference on Communications.

[41]  L. Milstein,et al.  An Analysis of a Real-Time Transform Domain Filtering Digital Communication System - Part II: Wide-Band Interference Rejection , 1983, IEEE Transactions on Communications.

[42]  Laurence B. Milstein,et al.  Cognitive Radio Based Multi-User Resource Allocation in Mobile Ad Hoc Networks Using Multi-Carrier CDMA Modulation , 2008, IEEE Journal on Selected Areas in Communications.

[43]  Anant Sahai,et al.  The case for multiband sensing , 2007 .

[44]  Balasubramaniam Natarajan,et al.  Generation of correlated Rayleigh fading envelopes for spread spectrum applications , 2000, IEEE Communications Letters.

[45]  Alexander M. Wyglinski,et al.  Agile Radio Implementation of OFDM Physical Layer for Dynamic Spectrum Access Research , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[46]  Michael A. Temple,et al.  Cognitive radio - an adaptive waveform with spectral sharing capability , 2005, IEEE Wireless Communications and Networking Conference, 2005.

[47]  Jeffrey H. Reed,et al.  A new approach to signal classification using spectral correlation and neural networks , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[48]  Zhiqiang Wu,et al.  Reliable Modulation Classification at Low SNR Using Spectral Correlation , 2007, 2007 4th IEEE Consumer Communications and Networking Conference.

[49]  Glen Prescott,et al.  Performance metrics for low probability of intercept-communication system , 1993 .

[50]  Gerhard Fettweis,et al.  On multi-carrier code division multiple access (MC-CDMA) modem design , 1994, Proceedings of IEEE Vehicular Technology Conference (VTC).

[51]  Michael A. Temple,et al.  TDCS, OFDM, and MC-CDMA: a brief tutorial , 2005, IEEE Communications Magazine.

[52]  Robert F. Mills,et al.  A spectrally modulated, spectrally encoded analytic framework for carrier interferometry signals , 2006, IWCMC '06.

[53]  Y. Miyanaga,et al.  A study of dynamic reconfigurable FFT processor for OFDM based cognitive radio , 2007, 2007 International Symposium on Communications and Information Technologies.

[54]  H. Tang,et al.  Some physical layer issues of wide-band cognitive radio systems , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[55]  W. A. Brown,et al.  Computationally efficient algorithms for cyclic spectral analysis , 1991, IEEE Signal Processing Magazine.

[56]  R. Tandra,et al.  Fundamental limits on detection in low SNR under noise uncertainty , 2005, 2005 International Conference on Wireless Networks, Communications and Mobile Computing.

[57]  Alexander M. Wyglinski,et al.  An Efficient Implementation of NC-OFDM Transceivers for Cognitive Radios , 2006, 2006 1st International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[58]  Kang G. Shin,et al.  What and how much to gain by spectrum agility? , 2007, IEEE Journal on Selected Areas in Communications.

[59]  Michael A. Temple,et al.  Initial acquisition performance of a transform domain communication system: modeling and simulation results , 2000, MILCOM 2000 Proceedings. 21st Century Military Communications. Architectures and Technologies for Information Superiority (Cat. No.00CH37155).

[60]  James O'Daniell Neel,et al.  Analysis and Design of Cognitive Radio Networks and Distributed Radio Resource Management Algorithms , 2006 .

[61]  Marcus L. Roberts,et al.  A General Framework for Analyzing, Characterizing, and Implementing Spectrally Modulated, Spectrally Encoded Signals , 2006 .

[62]  Zhiqiang Wu,et al.  Modulation Recognition in Multipath Fading Channels Using Cyclic Spectral Analysis , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[63]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[64]  Zhiqiang Wu,et al.  High-throughput, high-performance OFDM via pseudo-orthogonal carrier interferometry spreading codes , 2003, IEEE Trans. Commun..

[65]  Chiew Tong Lau,et al.  An Adaptive Waveform Generation Technique for Cognitive Radio , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.

[66]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[67]  Friedrich Jondral,et al.  Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency , 2004, IEEE Communications Magazine.

[68]  Brian M. Sadler,et al.  A Survey of Dynamic Spectrum Access , 2007, IEEE Signal Processing Magazine.

[69]  Zhiqiang Wu,et al.  Narrowband interference rejection in OFDM via carrier interferometry spreading codes , 2005, IEEE Transactions on Wireless Communications.

[70]  Matti Latva-aho,et al.  On the UWB system coexistence with GSM900, UMTS/WCDMA, and GPS , 2002, IEEE J. Sel. Areas Commun..

[71]  Jean-Paul M. G. Linnartz,et al.  Multi-Carrier Cdma In Indoor Wireless Radio Networks , 1994 .

[72]  Joseph Mitola,et al.  The software radio architecture , 1995, IEEE Commun. Mag..

[73]  Anant Sahai,et al.  Cooperative Sensing among Cognitive Radios , 2006, 2006 IEEE International Conference on Communications.

[74]  Michael A. Temple,et al.  Wavelet domain communication system: bit error sensitivity characterization for geographically separated transceivers (U) , 2002, MILCOM 2002. Proceedings.

[75]  Zhiqiang Wu,et al.  Overcoming peak-to-average power ratio issues in OFDM via carrier-interferometry codes , 2001, IEEE 54th Vehicular Technology Conference. VTC Fall 2001. Proceedings (Cat. No.01CH37211).

[76]  William A. Gardner,et al.  Measurement of spectral correlation , 1986, IEEE Trans. Acoust. Speech Signal Process..

[77]  Ryan W. Thomas,et al.  Cognitive networks , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[78]  Behrouz Farhang-Boroujeny,et al.  Multicarrier communication techniques for spectrum sensing and communication in cognitive radios , 2008, IEEE Communications Magazine.