A Survey on Approximations of One-Dimensional Gaussian Q-Function

Predicting the digital communication system performance plays a very important role in the process of system design. This performance is usually quantified by symbol error probability or bit error probability. Computing these probabilities in presence of Additive White Gaussian Noise requires to work with integrals involving the Gaussian Qfunction, which cannot be expressed in closed-form in terms of elementary functions. As a result, approximating the Gaussian Q-function in closed-form expressions with high accuracy becomes a necessity. In this paper, we give an overview about the Gaussian Q-function approximations and via some illustrating examples, we discuss their accuracy, tractability as well as their computational complexit

Cognitive Radio Systems: Performance Analysis and Optimal Resource Allocation

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

Approximations for Performance Analysis in Wireless Communications and Applications to Reconfigurable Intelligent Surfaces

In the last few decades, the field of wireless communications has witnessed significant technological advancements to meet the needs of today’s modern world. The rapidly emerging technologies, however, are becoming increasingly sophisticated, and the process of investigating their performance and assessing their applicability in the real world is becoming more challenging. That has aroused a relatively wide range of solutions in the literature to study the performance of the different communication systems or even draw new results that were difficult to obtain. These solutions include field measurements, computer simulations, and theoretical solutions such as alternative representations, approximations, or bounds of classic functions that commonly appear in performance analyses. Field measurements and computer simulations have significantly improved performance evaluation in communication theory. However, more advanced theoretical solutions can be further developed in order to avoid using the ex- pensive and time-consuming wireless communications measurements, replace the numerical simulations, which can sometimes be unreliable and suffer from failures in numerical evaluation, and achieve analytically simpler results with much higher accuracy levels than the existing theoretical ones. To this end, this thesis firstly focuses on developing new approximations and bounds using unified approaches and algorithms that can efficiently and accurately guide researchers through the design of their adopted wireless systems and facilitate the conducted performance analyses in the various communication systems. Two performance measures are of primary interest in this study, namely the average error probability and the ergodic capacity, due to their valuable role in conducting a better understanding of the systems’ behavior and thus enabling systems engineers to quickly detect and resolve design issues that might arise. In particular, several parametric expressions of different analytical forms are developed to approximate or bound the Gaussian Q-function, which occurs in the error probability analysis. Additionally, any generic function of the Q-function is approximated or bounded using a tractable exponential expression. Moreover, a unified logarithmic expression is proposed to approximate or bound the capacity integrals that occur in the capacity analysis. A novel systematic methodology and a modified version of the classical Remez algorithm are developed to acquire optimal coefficients for the accompanying parametric approximation or bound in the minimax sense. Furthermore, the quasi-Newton algorithm is implemented to acquire optimal coefficients in terms of the total error. The average symbol error probability and ergodic capacity are evaluated for various applications using the developed tools. Secondly, this thesis analyzes a couple of communication systems assisted with reconfigurable intelligent surfaces (RISs). RIS has been gaining significant attention lately due to its ability to control propagation environments. In particular, two communication systems are considered; one with a single RIS and correlated Rayleigh fading channels, and the other with multiple RISs and non-identical generic fading channels. Both systems are analyzed in terms of outage probability, average symbol error probability, and ergodic capacity, which are derived using the proposed tools. These performance measures reveal that better performance is achieved when assisting the communication system with RISs, increasing the number of reflecting elements equipped on the RISs, or locating the RISs nearer to either communication node. In conclusion, the developed approximations and bounds, together with the optimized coefficients, provide more efficient tools than those available in the literature, with richer capabilities reflected by the more robust closed-form performance analysis, significant increase in accuracy levels, and considerable reduction in analytical complexity which in turns can offer more understanding into the systems’ behavior and the effect of the different parameters on their performance. Therefore, they are expected to lay the groundwork for the investigation of the latest communication technologies, such as RIS technology, whose performance has been studied for some system models in this thesis using the developed tools

Explicitly Invertible Approximations of the Gaussian Q-Function: A Survey

Communications and information theory use the Gaussian $Q$ -function, a positive and decreasing function, across the literature. Its approximations were created to simplify mathematical study of the Gaussian $Q$ -function expressions. This is important since the $Q$ -function cannot be represented in closed-form terms of elementary functions. In a noise model with the Gaussian distribution function and various digital modulation schemes, closed-form approximations of the Gaussian $Q$ -function are used to predict a digital communications system's symbol error probability (SEP) or bit error probability (BEP). Another significant scenario pertains to fading channels, whereby it is important to accurately determine, through a closed-form expression, the precise evaluations of complex integrals involved in the computations of SEP or BEP. In addition to the aforementioned scenarios, it is imperative for a communications system designer to ascertain the requisite operational signal-to-noise ratio for the specific application, based on the target SEP (or BEP). In this scenario, the crucial role of the explicit invertibility of the Gaussian $Q$ -function approximation is of significant importance in achieving this objective. In this paper we propose a survey of the approximations of the Gaussian $Q$ -function found in the literature, reviewing also the approximations originally given for the 4 classical special functions related to it, restricting the analysis to the explicitly invertible ones, and classifying them on the basis of their accuracy (on the significant range), simplicity, and easiness of inversion, also distinguishing the bounds from approximations. We also list the inverses of some of them, already published or newly found in this research

Design and analysis of wireless diversity system

Ph.DDOCTOR OF PHILOSOPH

Razvoj metoda i algoritama za procenu performansi komunikacionih sistema primenom aproksimacija specijalnih funkcija

The intensive development of wireless communication systems has been accompanied by the need to develop methods and algorithms for implementing appropriate approximations of special functions in order to efficiently estimate the corresponding performance of these services through their application. In order to evaluate the behavior of digital communications systems, it is necessary to estimate standard performance measures for the observed wireless communications systems, various modulation types application, detection types, as well as channel models, and observe relations between performance and key values of system parameters. The analysis of the average bit error rate at reception for the applied modulation format is one of the tools for assessing service performance, that describes the nature of the wireless communication system in the best manner. In order to analytically evaluate the average bit error rate for the applied modulation format, it is necessary to perform the most accurate implementation of the approximation of special functions erfc(x), erf (x), Marcum Q, in the widest input range values. The dissertation will present composite methods of the special functions’ approximations. In addition to the simplicity of realization in approximating the observed functions, the aspect of robustness of approximations absolute and relative error values in a wide range of input parameters values will be considered. The advantages of the proposed solutions will be highlighted by direct comparison with the absolute and relative errors obtained by using the known special functions’ approximations from the literature. Furthermore, when transferring information through fading communication channels, for cases of application of proposed special functions’ approximations, it will be proved that system performance can be determined more easily by applying solutions proposed in the dissertation. In this way, it would be easier to determine the probability of the error of communication systems due to different types of fading existance in the channel. By comparing predicted values of the average bit error rate at reception, when transmitting signals through various communication channels medias, for cases of application of existing, previously proposed special functions’ approximations, with the average bit error rate at reception obtained by calculation based on the proposed approximation solutions, it will be shown that communication performances can be calculated more precisely. Proposed approximations could also be used in the source coding of the signal and could simplify design and realization of the quantizers

Analytical Characterization and Optimum Detection of Nonlinear Multicarrier Schemes

It is widely recognized that multicarrier systems such as orthogonal frequency division multiplexing (OFDM) are suitable for severely time-dispersive channels. However, it is also recognized that multicarrier signals have high envelope fluctuations which make them especially sensitive to nonlinear distortion effects. In fact, it is almost unavoidable to have nonlinear distortion effects in the transmission chain. For this reason, it is essential to have a theoretical, accurate characterization of nonlinearly distorted signals not only to evaluate the corresponding impact of these distortion effects on the system’s performance, but also to develop mechanisms to combat them. One of the goals of this thesis is to address these challenges and involves a theoretical characterization of nonlinearly distorted multicarrier signals in a simple, accurate way. The other goal of this thesis is to study the optimum detection of nonlinearly distorted, multicarrier signals. Conventionally, nonlinear distortion is seen as a noise term that degrades the system’s performance, leading even to irreducible error floors. Even receivers that try to estimate and cancel it have a poor performance, comparatively to the performance associated to a linear transmission, even with perfect cancellation of nonlinear distortion effects. It is shown that the nonlinear distortion should not be considered as a noise term, but instead as something that contains useful information for detection purposes. The adequate receiver to take advantage of this information is the optimum receiver, since it makes a block-by-block detection, allowing us to exploit the nonlinear distortion which is spread along the signal’s band. Although the optimum receiver for nonlinear multicarrier schemes is too complex, due to its necessity to compare the received signal with all possible transmitted sequences, it is important to study its potential performance gains. In this thesis, it is shown that the optimum receiver outperforms the conventional detection, presenting gains not only relatively to conventional receivers that deal with nonlinear multicarrier signals, but also relatively to conventional receivers that deal with linear, multicarrier signals. We also present sub-optimum receivers which are able to approach the performance gains associated to the optimum detection and that can even outperform the conventional linear, multicarrier schemes