Browsing by Subject "Linearization"
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Item Open Access Adaptive digital predistortion for linearization of power amplifier(Bilkent University, 2009) Şekerlisoy, BurakIn most communication systems, power amplifiers are used to obtain high output power. The nonlinear characteristics of the power amplifier leads to the distortion of the output signal. This distortion affects the efficiency of the power amplifier. The way to reduce this effect is to linearize the power amplifier near the saturation region where it is nonlinear. The widely used technique for the linearization of power amplifiers is predistortion. The proposed technique for predistortion uses a LUT(look-up-table), a complex multiplier, an address calculator, delay elements and an adaptation logic. A new adaptation logic to update the LUT coefficients, is used. The predistorter is simulated in Matlab software using a baseband model for the power amplifier. 16-QAM baseband modulation is used to simulate the predistorter. In order to see the performance of the proposed predistorter, hardware logic is implemented in FPGA and experimental setup with RF circuits and RF power amplifier is used. For different LUT sizes, the algorithm is tested and for the LUT size of 64, nearly 15 dB improvement in power spectrum is observed. The LUT size of 64 is observed to be the optimal LUT size in the experiments.Item Open Access Adaptive digital predistortion for power amplifier linearization(Bilkent University, 2008) Aslan, Makbule PehlivanHigh power amplification of linear modulation schemes which exhibit fluctuating envelopes, invariably leads to the generation of distortion and intermodulation products. In order to avoid these effects, maintaining both power and spectral efficiency, it is necessary to use linearization techniques. By using linearization techniques, the amplifier can be operated near the saturation with good efficiency and linearity. The technique proposed here is predistortion based on a look-up table (LUT) method using input and output signal envelopes. The predistortion is implemented using a LUT and an address generation block that selects the appropriate coefficient from the LUT, given the magnitude of the input signal. The testing of the predistorter is done by using a baseband system model which consists of a 16-QAM modulator, an upsampler, a raised cosine filter, the predistorter and a baseband behavioural amplifier model. The performance of the predistorter with a new LUT update method is evaluated in terms of power efficiency and spectrum efficiency. MATLAB simulations show that to obtain up to 25-30 dB improvement in power spectrum is possible and sufficiently large LUT size is needed to reduce the background noise level. Furthermore, the performance of the predistorter in the case of an amplifier with memory is also investigated. The algorithms have been implemented on an FPGA chip. The performance of the system is as predicted in MATLAB simulations.Item Open Access A branch-and-cut algorithm for quadratic assignment problems based on linearizations(Elsevier, 2007-04) Erdoğan, G.; Tansel, B.The quadratic assignment problem (QAP) is one of the hardest combinatorial optimization problems known. Exact solution attempts proposed for instances of size larger than 15 have been generally unsuccessful even though successful implementations have been reported on some test problems from the QAPLIB up to size 36. In this study, we focus on the Koopmans–Beckmann formulation and exploit the structure of the flow and distance matrices based on a flow-based linearization technique that we propose. We present two new IP formulations based on the flow-based linearization technique that require fewer variables and yield stronger lower bounds than existing formulations. We strengthen the formulations with valid inequalities and report computational experience with a branch-and-cut algorithm. The proposed method performs quite well on QAPLIB instances for which certain metrics (indices) that we proposed that are related to the degree of difficulty of solving the problem are relatively high (⩾0.3⩾0.3). Many of the well-known instances up to size 25 from the QAPLIB (e.g. nug24, chr25a) are in this class and solved in a matter of days on a single PC using the proposed algorithm.Item Open Access Enhancements to linear least squares localization through reference selection and ML estimation(IEEE, 2008-03-04) Güvenç, İsmail; Gezici, Sinan; Watanabe F.; Inamura, H.Linear least squares (LLS) estimation is a low complexity but sub-optimum method for estimating the location of a mobile terminal (MT) from some distance measurements. It requires selecting one of the fixed terminals (FTs) as a reference FT for obtaining a linear set of expressions. However, selection of the reference FT is commonly performed arbitrarily in the literature. In this paper, a method for selection of the reference FT is proposed, which improves the location accuracy compared to a fixed selection of the reference FT. Moreover, a covariancematrix based LLS estimator is proposed in line of sight (LOS) and non-LOS (NLOS) environments which further improves accuracy since the correlations between the observations are exploited. Simulation results prove the effectiveness of the proposed techniques. © 2008 IEEE.Item Open Access Exact algorithms for the joint object placement and request routing problem in content distribution networks(2008) Bektaş, T.; Cordeau J.-F.; Erkut, E.; Laporte G.This paper describes two exact algorithms for the joint problem of object placement and request routing in a content distribution network (CDN). A CDN is a technology used to efficiently distribute electronic content throughout an existing Internet Protocol network. The problem consists of replicating content on the proxy servers and routing the requests for the content to a suitable proxy server in a CDN such that the total cost of distribution is minimized. An upper bound on end-to-end object transfer time is also taken into account. The problem is formulated as a nonlinear integer programming formulation which is linearized in three different ways. Two algorithms, one based on Benders decomposition and the other based on Lagrangean relaxation and decomposition, are described for the solution of the problem. Computational experiments are conducted by comparing the proposed linearizations and the two algorithms on randomly generated Internet topologies. © 2007 Elsevier Ltd. All rights reserved.Item Open Access Expected gain-loss pricing and hedging of contingent claims in incomplete markets by linear programming(Elsevier, 2010) Pınar, M. Ç.; Salih, A.; Camcı, A.We analyze the problem of pricing and hedging contingent claims in the multi-period, discrete time, discrete state case using the concept of a "λ gain-loss ratio opportunity". Pricing results somewhat different from, but reminiscent of, the arbitrage pricing theorems of mathematical finance are obtained. Our analysis provides tighter price bounds on the contingent claim in an incomplete market, which may converge to a unique price for a specific value of a gain-loss preference parameter imposed by the market while the hedging policies may be different for different sides of the same trade. The results are obtained in the simpler framework of stochastic linear programming in a multi-period setting, and have the appealing feature of being very simple to derive and to articulate even for the non-specialist. They also extend to markets with transaction costs.Item Open Access An ILP formulation for application mapping onto Network-on-Chips(IEEE, 2009) Tosun, S.; Öztürk, Özcan; Ozen, M.Ever shrinking technologies in VLSI era made it possible to place several modules onto a single die. However, the need for the new communication methods has also increased dramatically since traditional bus-based systems suffer from signal propagation delays, signal integrity, and scalability. Network-on-Chip (NoC) is the biggest step towards the communication bottleneck of System-on-Chip (SoC) architectures. In this paper, we present an Integer Linear Programming (ILP) formulation for application mapping onto mesh based Network-on-Chips to minimize the energy consumption of the system. The proposed method obtains optimal or close to optimal results within the given computation time limit. We also experimentally investigate the impact of the size of the mesh architecture on the application mapping and total communication. ©2009 IEEE.Item Open Access Integral action based Dirichlet boundary control of Burgers equation(IEEE, 2003) Efe, M. Ö.; Özbay, HitayModeling and boundary control for Burgers Equation is studied in this paper. Modeling has been done via processing of numerical observations through singular value decomposition with Galerkin projection. This results in a set of spatial basis functions together with a set of Ordinary Differential Equations (ODEs) describing the temporal evolution. Since the dynamics described by Burgers equation is nonlinear, the corresponding reduced order dynamics turn out to be nonlinear. The presented analysis explains how boundary condition appears as a control input in the ODEs. The controller design is based on the linearization of the dynamic model. It has been demonstrated that an integral controller, whose gain is a function of the spatial variable, is sufficient to observe reasonably high tracking performance with a high degree of robustness.Item Open Access On the single-assignment p-hub center problem(Elsevier, 2000) Kara, B. Y.; Tansel, B. Ç.We study the computational aspects of the single-assignment p-hub center problem on the basis of a basic model and a new model. The new model's performance is substantially better in CPU time than different linearizations of the basic model. We also prove the NP-Hardness of the problem.Item Open Access Power amplifier linearization by predistortion(Bilkent University, 2006) Durukal, MustafaPower amplifiers are important elements in communication systems but they are inherently nonlinear. This nonlinearity shows itself in the form of amplitude and phase distortion. One way to get rid of this nonlinear behaviour is to apply backoff which means to operate the amplifier at an output power smaller than its saturated output power. As the backoff is increased, the amplifier will behave more linearly. But this will also reduce the efficiency of the amplifier, which is undesirable. This tradeoff between efficiency and linearity is solved by linearization techniques. By using linearization techniques, the amplifier can be operated near to saturation with good efficiency and linearity. This thesis focuses on polar polynomial predistortion and polar look-up table predistortion, which are popular linearization techniques. A polar polynomial predistorter and a polar look-up table predistorter are implemented and tested with simulations in software. The implementation and testing is done by using IT++ which is a C++ library of mathematical, signal processing, speech processing, and communications classes and functions. The testing of the predistorters is done by using a baseband system model which consists of a 16-QAM modulator, an upsampler, a raised cosine filter, the predistorter and a baseband behavioural amplifier model. The performance of the predistorters is evaluated in terms of adjacent channel power ratio, AM/AM & AM/PM responses and BER under AWGN. Simulation results show that the predistorters have good performance. In the simulations, the polar polynomial predistorter achieved 20 dB reduction and the polar look-up table predistorter achieved 25 dB reduction in adjacent channel power ratio. The effect of polynomial order and table size on the performance of the predistorters is investigated. Furthermore, the effect of lowpass filtering on the performance of the predistorters is also investigated by placing a lowpass filter after the predistorters in the system model. It is observed that as the ratio of the bandwidth of the lowpass filter to the bandwidth of the raised cosine filter decreases, the negative effect of the lowpass filter on the performance of the predistorters increases.Item Open Access Quadratic assignment problem : linearizations and polynomial time solvable cases(Bilkent University, 2006) Erdoğan, GüneşThe Quadratic Assignment Problem (QAP) is one of the hardest combinatorial optimization problems known. Exact solution attempts proposed for instances of size larger than 15 have been generally unsuccessful even though successful implementations have been reported on some test problems from the QAPLIB up to size 36. In this dissertation, we analyze the binary structure of the QAP and present new IP formulations. We focus on “flow-based” formulations, strengthen the formulations with valid inequalities, and report computational experience with a branch-and-cut algorithm. Next, we present new classes of instances of the QAP that can be completely or partially reduced to the Linear Assignment Problem and give procedures to check whether or not an instance is an element of one of these classes. We also identify classes of instances of the Koopmans-Beckmann form of the QAP that are solvable in polynomial time. Lastly, we present a strong lower bound based on Bender’s decomposition.Item Open Access The single-assignment hub covering problem: models and linearizations(Palgrave Macmillan Ltd., 2003) Kara, B. Y.; Tansel, B. C.We study the hub covering problem which, so far, has remained one of the unstudied hub location problems in the literature. We give a combinatorial and a new integer programming formulation of the hub covering problem that is different from earlier integer programming formulations. Both new and old formulations are nonlinear binary integer programs. We give three linearizations for the old model and one linearization for the new one and test their computational performances based on 80 instances of the CAB data set. Computational results indicate that the linear version of the new model performs significantly better than the most successful linearization of the old model both in terms of average and maximum CPU times as well as in core storage requirements.