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 are presented. Finally, the benefits of combining overlay/underlay techniques to improve spectrum efficiency and maximize channel capacity are addressed

A General Framework for Analyzing, Characterizing, and Implementing Spectrally Modulated, Spectrally Encoded Signals

Fourth generation (4G) communications will support many capabilities while providing universal, high speed access. One potential enabler for these capabilities is software defined radio (SDR). When controlled by cognitive radio (CR) principles, the required waveform diversity is achieved via a synergistic union called CR-based SDR. Research is rapidly progressing in SDR hardware and software venues, but current CR-based SDR research lacks the theoretical foundation and analytic framework to permit efficient implementation. This limitation is addressed here by introducing a general framework for analyzing, characterizing, and implementing spectrally modulated, spectrally encoded (SMSE) signals within CR-based SDR architectures. Given orthogonal frequency division multiplexing (OFDM) is a 4G candidate signal, OFDM-based signals are collectively classified as SMSE since modulation and encoding are spectrally applied. The proposed framework provides analytic commonality and unification of SMSE signals. Applicability is first shown for candidate 4G signals, and resultant analytic expressions agree with published results. Implementability is then demonstrated in multiple coexistence scenarios via modeling and simulation to reinforce practical utility

Spectrally Modulated Spectrally Encoded Framework Based Cognitive Radio in Mobile Environment

Radio spectrum has become a precious resource, and it has long been the dream of wireless communication engineers to maximize the utilization of the radio spectrum. Dynamic Spectrum Access (DSA) and Cognitive Radio (CR) have been considered promising to enhance the efficiency and utilization of the spectrum. Since some of the spectrum bands are occupied by primary users (PUs), the available spectrum for secondary users (SUs) are non-contiguous, and multi-carrier transmission technologies become the natural solution to occupy those non-contiguous bands. Non-contiguous multi-carrier based modulations, such as NC-OFDM (non-contiguous Orthogonal Frequency Division Multiplexing), NC-MC-CDMA (non-contiguous multi-carrier code division multiple access) and NC-SC-OFDM (non-contiguous single carrier OFDM), allow the SUs to utilize the available spectrum. Spectrally Modulated Spectrally Encoded (SMSE) framework offers a general framework to generate multi-carrier based waveform for CR. However, it is well known that all multi-carrier transmission technologies suffer significant performance degradation resulting from inter-carrier interference (ICI) in high mobility environments. Current research work in cognitive radio has not sufficiently considered and addressed this issue yet. Hence, it is highly desired to study the effect of mobility on CR communication systems and how to improve the performance through affordable low-complexity signal processing techniques. In this dissertation, we analyze the inter-carrier interference for SMSE based multi-carrier transmissions in CR, and propose multiple ICI mitigation techniques and carrier frequency offset (CFO) estimator. Specifically, (1) an ICI self-cancellation algorithm is adapted to the MC-CDMA system by designing new spreading codes to enable the system with the capability to reduce the ICI; (2) a blind ICI cancellation technique named Total ICI Cancellation is proposed to perfectly remove the ICI effect for OFDM and MC-CDMA systems and provide the performance approximately identical to that of the systems without ICI; (3) a novel modulation scheme, called Magnitude Keyed Modulation (MKM), is proposed to combine with SC-OFDM system and provide ICI immunity feature so that the system performance is not affected by the mobility or carrier frequency offset; (4) a blind carrier frequency offset estimation algorithm is proposed to accurately estimate the CFO; (5) finally, compared to traditional ICI analysis and cancellation techniques with assumption of constant carrier frequency offset among all the subcarriers, subcarrier varying CFO scenario is considered for the wideband multi-carrier transmission and non-contiguous multi-carrier transmission for CR, and an ICI total cancellation algorithm is proposed for the multi-carrier system with subcarrier varying CFOs to entirely remove the ICI

Spectrally Modulated Spectrally Encoded Framework Based Cognitive Radio in Mobile Environment

Radio spectrum has become a precious resource, and it has long been the dream of wireless communication engineers to maximize the utilization of the radio spectrum. Dynamic Spectrum Access (DSA) and Cognitive Radio (CR) have been considered promising to enhance the efficiency and utilization of the spectrum. Since some of the spectrum bands are occupied by primary users (PUs), the available spectrum for secondary users (SUs) are non-contiguous, and multi-carrier transmission technologies become the natural solution to occupy those non-contiguous bands. Non-contiguous multi-carrier based modulations, such as NC-OFDM (non-contiguous Orthogonal Frequency Division Multiplexing), NC-MC-CDMA (non-contiguous multi-carrier code division multiple access) and NC-SC-OFDM (non-contiguous single carrier OFDM), allow the SUs to utilize the available spectrum. Spectrally Modulated Spectrally Encoded (SMSE) framework offers a general framework to generate multi-carrier based waveform for CR. However, it is well known that all multi-carrier transmission technologies suffer significant performance degradation resulting from inter-carrier interference (ICI) in high mobility environments. Current research work in cognitive radio has not sufficiently considered and addressed this issue yet. Hence, it is highly desired to study the effect of mobility on CR communication systems and how to improve the performance through affordable low-complexity signal processing techniques. In this dissertation, we analyze the inter-carrier interference for SMSE based multi-carrier transmissions in CR, and propose multiple ICI mitigation techniques and carrier frequency offset (CFO) estimator. Specifically, (1) an ICI self-cancellation algorithm is adapted to the MC-CDMA system by designing new spreading codes to enable the system with the capability to reduce the ICI; (2) a blind ICI cancellation technique named Total ICI Cancellation is proposed to perfectly remove the ICI effect for OFDM and MC-CDMA systems and provide the performance approximately identical to that of the systems without ICI; (3) a novel modulation scheme, called Magnitude Keyed Modulation (MKM), is proposed to combine with SC-OFDM system and provide ICI immunity feature so that the system performance is not affected by the mobility or carrier frequency offset; (4) a blind carrier frequency offset estimation algorithm is proposed to accurately estimate the CFO; (5) finally, compared to traditional ICI analysis and cancellation techniques with assumption of constant carrier frequency offset among all the subcarriers, subcarrier varying CFO scenario is considered for the wideband multi-carrier transmission and non-contiguous multi-carrier transmission for CR, and an ICI total cancellation algorithm is proposed for the multi-carrier system with subcarrier varying CFOs to entirely remove the ICI

Reducing the Peak to Average Power Ratio of LDS-OFDM signals

Low Density Signature-Orthogonal Frequency Division Multiplexing (LDS-OFDM) has been introduced recently as an efficient multiple access technique. High Peak to Average Power Ratio (PAPR) is an important obstacle to multicarrier communication systems. This paper concentrates on the PAPR investigation and its reduction for LDS-OFDM signals. Specifically, we will investigate the impact of subcarrier allocation schemes and the phases of the signatures on the PAPR of LDS-OFDM signals. Firstly, the PAPR of LDS-OFDM with conventional signatures is investigated. Then we propose two methods for PAPR reduction; Newman phases and DFT pre-coding. The former method is simple and doesn't imply changes in the system structure while the DFT pre-coding implies a modification in the system. Simulation results show that using Newman phases considerably reduces the PAPR of LDS-OFDM. Further PAPR reduction is achieved using DFT pre-coded LDS-OFDM on the cost of higher complexity

Multi-user detection for multi-carrier communication systems

Doctor of PhilosophyDepartment of Electrical and Computer EngineeringBalasubramaniam NatarajanWireless broadband communications is a rapidly growing industry. New enabling technologies such as multi-carrier code division multiple access (MC-CDMA) are shaping the future of wireless systems. However, research efforts in improving MC-CDMA receiver performance have received limited attention and there is a need for innovative receiver designs for next generation MC-CDMA. In this thesis, we propose novel multi-user detection (MUD) schemes to enhance the performance of both synchronous and asynchronous MC-CDMA. First, we adapt the ant colony optimization (ACO) approach to solve the optimal MUD problem in MC-CDMA systems. Our simulations indicate that the ACO based MUD converges to the optimal BER performance in relatively few iterations providing more that 95% savings in computational complexity. Second, we propose a new MUD structure specifically for asynchronous MC-CDMA. Previously proposed MUDs for asynchronous MC-CDMA perform the detection for one user (desired user) at a time, mandating multiple runs of the algorithm to detect all users' symbols. In this thesis, for the first time we present a MUD structure that detects all users' symbols simultaneously in one run by extending the receiver's integration window to capture the energy scattered in two consecutive symbol durations. We derive the optimal, decorrelator and minimum mean square error (MMSE) MUD for the extended window case. Our simulations demonstrate that the proposed MUD structures not only perform similar to a MUD that detects one user at a time, but its computational complexity is significantly lower. Finally, we extend the MUD ideas to multicarrier implementation of single carrier systems. Specifically, we employ the novel MUD structure as a multi-symbol detection scheme in CI-CDMA and illustrate the resulting performance gain via simulations