354 research outputs found

    Cognitive Radio Systems: Performance Analysis and Optimal Resource Allocation

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    Rapid growth in the use of wireless services coupled with inefficient utilization of scarce spectrum resources has led to the analysis and development of cognitive radio systems. Cognitive radio systems provide dynamic and more efficient utilization of the available spectrum by allowing unlicensed users (i.e., cognitive or secondary users) to access the frequency bands allocated to the licensed users (i.e., primary users) without causing harmful interference to the primary user transmissions. The central goal of this thesis is to conduct a performance analysis and obtain throughput- and energy-efficient optimal resource allocation strategies for cognitive radio systems. Cognitive radio systems, which employ spectrum sensing mechanisms to learn the channel occupancy by primary users, generally operate under sensing uncertainty arising due to false alarms and miss-detections. This thesis analyzes the performance of cognitive radio systems in a practical setting with imperfect spectrum sensing. In the first part of the thesis, optimal power adaptation schemes that maximize the achievable rates of cognitive users with arbitrary input distributions in underlay cognitive radio systems subject to transmit and interference power constraints are studied. Simpler approximations of optimal power control policies in the low-power regime are determined. Low-complexity optimal power control algorithms are proposed. Next, energy efficiency is considered as the performance metric and power allocation strategies that maximize the energy efficiency of cognitive users in the presence of time-slotted primary users are identified. The impact of different levels of channel knowledge regarding the transmission link between the secondary transmitter and secondary receiver, and the interference link between the secondary transmitter and primary receiver on the optimal power allocation is addressed. In practice, the primary user may change its status during the transmission phase of the secondary users. In such cases, the assumption of time-slotted primary user transmission no longer holds. With this motivation, the spectral and energy efficiency in cognitive radio systems with unslotted primary users are analyzed and the optimal frame duration and energy-efficient optimal power control schemes subject to a collision constraint are jointly determined. The second line of research in this thesis focuses on symbol error rate performance of cognitive radio transmissions in the presence of imperfect sensing decisions. General formulations for the optimal decision rule and error probabilities for arbitrary modulation schemes are provided. The optimal decision rule for rectangular quadrature amplitude modulation (QAM) is characterized, and closed-form expressions for the average symbol error probability attained with the optimal detector under both transmit power and interference constraints are derived. Furthermore, throughput of cognitive radio systems for both fixed-rate and variable-rate transmissions in the finite-blocklength regime is studied. The maximum constant arrival rates that the cognitive radio channel can support with finite blocklength codes while satisfying statistical quality of service (QoS) constraints imposed as limitations on the buffer violation probability are characterized. In the final part of the thesis, performance analysis in the presence of QoS requirements is extended to general wireless systems, and energy efficiency and throughput optimization with arbitrary input signaling are studied when statistical QoS constraints are imposed as limitations on the buffer violation probability. Effective capacity is chosen as the performance metric to characterize the maximum throughput subject to such buffer constraints by capturing the asymptotic decay-rate of buffer occupancy. Initially, constant-rate source is considered and subsequently random arrivals are taken into account

    Bit Loading and Peak Average Power Reduction Techniques for Adaptive Orthogonal Frequency Division Multiplexing Systems

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    In a frequency-selective channel a large number of resolvable multipaths are present which lead to the fading of the signal. Orthogonal frequency division multiplexing (OFDM) is well-known to be effective against multipath distortion. It is a multicarrier communication scheme, in which the bandwidth of the channel is divided into subcarriers and data symbols are modulated and transmitted on each subcarrier simultaneously. By inserting guard time that is longer than the delay spread of the channel, an OFDM system is able to mitigate intersymbol interference (ISI). Significant improvement in performance is achieved by adaptively loading the bits on the subcarriers based on the channel state information from the receiver. Imperfect channel state information (CSI) arises from noise at the receiver and also due to the time delay in providing the information to the transmitter for the next data transmission. This thesis presents an investigation into the different adaptive techniques for loading the data bits on the subcarriers. The choice of the loading technique is application specific. The spectral efficiency and the bit error rate (BER) performance of adaptive OFDM as well as the implementation complexity of the different loading algorithms is studied by varying any one of the parameters, data rate or BER or total transmit power subject to the constraints on the other two. A novel bit loading algorithm based on comparing the SNR with the threshold in order to minimize the BER is proposed and its performance for different data rates is plotted. Finally, this thesis presents a method for reducing the large peak to average power ratio (PAPR) problem with OFDM which arises when the sinusoidal signals of the subcarriers add constructively. The clipping and the probabilistic approaches were studied. The probabilistic technique shows comparatively better BER performance as well as reduced PAPR ratio but is more complex to implement

    Effective Capacity in Multiple Access Channels with Arbitrary Inputs

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    In this paper, we consider a two-user multiple access fading channel under quality-of-service (QoS) constraints. We initially formulate the transmission rates for both transmitters, where the transmitters have arbitrarily distributed input signals. We assume that the receiver performs successive decoding with a certain order. Then, we establish the effective capacity region that provides the maximum allowable sustainable arrival rate region at the transmitters' buffers under QoS guarantees. Assuming limited transmission power budgets at the transmitters, we attain the power allocation policies that maximize the effective capacity region. As for the decoding order at the receiver, we characterize the optimal decoding order regions in the plane of channel fading parameters for given power allocation policies. In order to accomplish the aforementioned objectives, we make use of the relationship between the minimum mean square error and the first derivative of the mutual information with respect to the power allocation policies. Through numerical results, we display the impact of input signal distributions on the effective capacity region performance of this two-user multiple access fading channel

    Transmit Power Minimization for MIMO Systems of Exponential Average BER with Fixed Outage Probability

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    This document is the Accepted Manuscript version of the following article: Dian-Wu Yue, and Yichuang Sun, ‘Transmit Power Minimization for MIMO Systems of Exponential Average BER with Fixed Outage Probability’, Wireless Personal Communications, Vol. 90 (4): 1951-1970, first available online on 20 June 2016. Under embargo. Embargo end date: 20 June 2017. The final publication is available at Springer via https://link.springer.com/article/10.1007%2Fs11277-016-3432-4This paper is concerned with a wireless multiple-antenna system operating in multiple-input multiple-output (MIMO) fading channels with channel state information being known at both transmitter and receiver. By spatiotemporal subchannel selection and power control, it aims to minimize the average transmit power (ATP) of the MIMO system while achieving an exponential type of average bit error rate (BER) for each data stream. Under the constraints on each subchannel that individual outage probability and average BER are given, based on a traditional upper bound and a dynamic upper bound of Q function, two closed-form ATP expressions are derived, respectively, which can result in two different power allocation schemes. Numerical results are provided to validate the theoretical analysis, and show that the power allocation scheme with the dynamic upper bound can achieve more power savings than the one with the traditional upper bound.Peer reviewe

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

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    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

    NOVEL OFDM SYSTEM BASED ON DUAL-TREE COMPLEX WAVELET TRANSFORM

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    The demand for higher and higher capacity in wireless networks, such as cellular, mobile and local area network etc, is driving the development of new signaling techniques with improved spectral and power efficiencies. At all stages of a transceiver, from the bandwidth efficiency of the modulation schemes through highly nonlinear power amplifier of the transmitters to the channel sharing between different users, the problems relating to power usage and spectrum are aplenty. In the coming future, orthogonal frequency division multiplexing (OFDM) technology promises to be a ready solution to achieving the high data capacity and better spectral efficiency in wireless communication systems by virtue of its well-known and desirable characteristics. Towards these ends, this dissertation investigates a novel OFDM system based on dual-tree complex wavelet transform (D
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