An Accurate Sample Rejection Estimator of the Outage Probability With Equal Gain Combining

We evaluate the outage probability (OP) for L-branch equal gain combining (EGC) receivers operating over fading channels, i.e., equivalently the cumulative distribution function (CDF) of the sum of the L channel envelopes. In general, closed form expressions of OP values are out of reach. The use of Monte Carlo (MC) simulations is not a good alternative as it requires a large number of samples for small values of OP. In this paper, we use the concept of importance sampling (IS), being known to yield accurate estimates using fewer simulation runs. Our proposed IS scheme is based on sample rejection where the IS density is the truncation of the underlying density over the L dimensional sphere. It assumes the knowledge of the CDF of the sum of the L channel gains in closed-form. Such an assumption is not restrictive since it holds for various challenging fading models. We apply our approach to the case of independent Rayleigh, correlated Rayleigh, and independent and identically distributed Rice fading models. Next, we extend our approach to the interesting scenario of generalised selection combining receivers combined with EGC under the independent Rayleigh environment. For each case, we prove the desired bounded relative error property. Finally, we validate these theoretical results through some selected experiments

Adaptive Transmission Schemes for Spectrum Sharing Systems: Trade-offs and Performance Analysis

Cognitive radio (CR) represents a key solution to the existing spectrum scarcity problem. Under the scenario of CR, spectrum sharing systems allow the coexistence of primary users (PUs) and secondary users (SUs) in the same spectrum as long as the interference from the secondary to the primary link stays below a given threshold. In this thesis, we propose a number of adaptive transmission schemes aiming at improving the performance of the secondary link in these systems while satisfying the interference constraint set by the primary receiver (PR). In the proposed techniques, the secondary transmitter (ST) adapts its transmission settings based on the availability of the channel state information (CSI) of the secondary and the interference links. In this context, these schemes offer different performance tradeoffs in terms of spectral efficiency, energy efficiency, and overall complexity. In the first proposed scheme, power adaptation (PA) and adaptive modulation (AM) are jointly used with switched transmit diversity in order to increase the capacity of the secondary link while minimizing the average number of antenna switching. Then, the concept of minimum-selection maximum ratio transmission (MS-MRT) is proposed as an adaptive variation of maximum ratio transmission (MRT) in a spectrum sharing scenario in order to maximize the capacity of the secondary link while minimizing the average number of transmit antennas. In order to achieve this performance, MS-MRT assumes that the secondary's CSI (SCSI) is perfectly known at the ST, which makes this scheme challenging from a practical point of view. To overcome this challenge, another transmission technique based on orthogonal space time bloc codes (OSTBCs) with transmit antenna selection (TAS) is proposed. This scheme uses the full-rate full-diversity Alamouti scheme in an underlay CR scenario in order to maximize the secondary's transmission rate. While the solutions discussed above offer a considerable improvement in the performance of spectrum sharing systems, they generally experience a high overall system complexity and are not optimized to meet the tradeoff between spectral efficiency and energy efficiency. In order to address this issue, we consider using spatial modulation (SM) in order to come with a spectrum sharing system optimized in terms spectral efficiency and energy efficiency. Indeed, SM can be seen as one of the emerging and promising new technologies optimizing the communication system while reducing the energy consumption thanks to the use of a single radio frequency (RF) chain for transmission. In this context, we propose the adaptive spatial modulation (ASM) scheme using AM in order to improve the spectral efficiency of SM. We also extend ASM to spectrum sharing systems by proposing a number of ASM-CR schemes aiming at improving the performance of these systems in terms of spectral efficiency and energy efficiency. While the use of a single RF-chain improves the energy efficiency of the above schemes, the RF-chain switching process between different transmissions comes with additional complexity and implementation issues. To resolve these issues, we use the concept of reconfigurable antennas (RAs) in order to improve the performance of space shift keying (SSK). In this context, employing RAs with SSK instead of conventional antennas allows for implementing only one RF chain and selecting different antenna-states for transmission without the need for RF switching. Moreover, the reconfigurable properties of RAs can be used as additional degrees of freedom in order to enhance the performance of SSK in terms of throughput, system complexity, and error performance. These RAs-based schemes are also extended to spectrum sharing systems in order to improve the capacity of the secondary link while reducing the energy consumption and the implementation complexity of the SU. In summary, we propose in this thesis several adaptive transmission schemes for spectrum sharing systems. The performance of each of these schemes is confirmed via Monte-Carlo simulations and analytical results and is shown to offer different tradeoffs in terms of spectral efficiency, energy efficiency, reliability, and implementation complexity. In this context, these proposed schemes offer different solutions in order to improve the performance of underlay cognitive radio systems

Performance analysis of energy detector over generalised wireless channels in cognitive radio

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.This thesis extensively analyses the performance of an energy detector which is widely employed to perform spectrum sensing in cognitive radio over different generalised channel models. In this analysis, both the average probability of detection and the average area under the receiver operating characteristic curve (AUC) are derived using the probability density function of the received instantaneous signal to noise ratio (SNR). The performance of energy detector over an ŋ --- µ fading, which is used to model the Non-line-of-sight (NLoS) communication scenarios is provided. Then, the behaviour of the energy detector over к --- µ shadowed fading channel, which is a composite of generalized multipath/shadowing fading channel to model the lineof- sight (LoS) communication medium is investigated. The analysis of the energy detector over both ŋ --- µ and к --- µ shadowed fading channels are then extended to include maximal ratio combining (MRC), square law combining (SLC) and square law selection (SLS) with independent and non-identically (i:n:d) diversity branches. To overcome the problem of mathematical intractability in analysing the energy detector over i:n:d composite fading channels with MRC and selection combining (SC), two different unified statistical properties models for the sum and the maximum of mixture gamma (MG) variates are derived. The first model is limited by the value of the shadowing severity index, which should be an integer number and has been employed to study the performance of energy detector over composite α --- µ /gamma fading channel. This channel is proposed to represent the non-linear prorogation environment. On the other side, the second model is general and has been utilised to analyse the behaviour of energy detector over composite ŋ --- µ /gamma fading channel. Finally, a special filter-bank transform which is called slantlet packet transform (SPT) is developed and used to estimate the uncertain noise power. Moreover, signal denoising based on hybrid slantlet transform (HST) is employed to reduce the noise impact on the performance of energy detector. The combined SPT-HST approach improves the detection capability of energy detector with 97% and reduces the total computational complexity by nearly 19% in comparison with previously implemented work using filter-bank transforms. The aforementioned percentages are measured at specific SNR, number of selected samples and levels of signal decompositionMartyrs Foundatio

Performance Analysis of Non-Ideal MIMO Systems in Fading Channels

En esta tesis se aborda el análisis de prestaciones de sistemas MIMO bajo ciertas condiciones no ideales. Se han considerado limitaciones realistas como son las interferencias co-canal, el canal de retorno con velocidad limitada, y la correlación espacial entre antenas. Bajo estas condiciones, se han analizado las probabilidades de error y de outage para sistemas MIMO que incluyen técnicas de conformación de haz en el transmisor y/o distintas técnicas de diversidad espacial en el receptor. Con el fin de obtener expresiones cerradas y exactas par los indicadores de rendimiento mencionados, se han desarrollo nuevos métodos o herramientas matemáticas que facilitan o, en algunos casos, hacen posible el análisis. En primer lugar, se han obtenido nuevas expresiones cerradas para las integrales del tipo Lipschitz-Hankel y para la distribución de los elementos de la diagonal de matrices Wishart complejas. Posteriormente, estos resultados han sido aplicados al análisis de prestaciones de distintos sistemas MIMO en condiciones no-ideales. Concretamente, se han obtenido nuevas expresiones cerrradas de la probabilidad de outage para: sistemas MRC con interferencia co-canal, sistemas MIMO con correlación espacial entre antenas, y sistemas MIMO MRC con un canal de retorno limitado en velocidad. Además, se han obtenido expresiones cerradas para la probabilidad de error en sistemas de diversidad en recepción que emplean modulaciones no coherentes y no ortogonales

Three Branch Diversity Systems for Multi-Hop IoT Networks

Internet of Things (IoT) is an emerging technological paradigm connecting numerous smart objects for advanced applications ranging from home automation to industrial control to healthcare. The rapid development of wireless technologies and miniature embedded devices has enabled IoT systems for such applications, which have been deployed in a variety of environments. One of the factors limiting the performance of IoT devices is the multipath fading caused by reflectors and attenuators present in the environment where these devices are deployed. Leveraging polarization diversity is a well-known technique to mitigate the deep signal fades and depolarization effects caused by multipath. However, neither experimental validation of the performance of polarization diversity antenna with more than two branches nor the potency of existing antenna selection techniques on such antennas in practical scenarios has received much attention. The objectives of this dissertation are threefold. First, to demonstrate the efficacy of a tripolar antenna, which is specifically designed for IoT devices, in harsh environments through simulations and experimental data. Second, to develop antenna selection strategies to utilize polarized signals received at the antenna, considering the restrictions imposed due to resource limitations of the IoT devices. Finally, to conduct comparative analyses on the existing standard diversity techniques and proposed approaches, in conjunction with experimental data. Accordingly, this dissertation presents the testing results of tripolar antenna integrated with Arduino based IoT devices deployed in environments likely to be experienced by IoT devices in real life applications. Both simulation and experimental results from single point-to-point wireless links demonstrate the advantage of utilizing tripolar antennas in harsh propagation conditions over single branch antenna. Motivated by these empirical results, we deploy a small-scale IoT network with tripolar antenna based nodes to analyze the impact of tripolar antenna on neighbor nodes performance as well as to investigate end-to-end network performance. This work illustrates that the selection of antenna branches, while considering network architecture and the level of congestion on the repeater nodes, minimizes excessive antenna switching and energy consumption. Similar results are shown for IoT networks with predetermined and dynamic routing protocols, where the proposed techniques yielded lower energy consumption than the conventional diversity schemes. Furthermore, a probabilistic, low complexity antenna selection approach based on Hidden Markov model is proposed and implemented on wireless sensor nodes aiming to reduce energy consumption and improve diversity gain. Finally, we develop a dual-hop based technique where a node selects the antenna element for optimal performance based on its immediate network neighbors antenna configuration status during selection. The performance of the proposed technique, which is verified through simulation and measured data, illustrates the importance of considering network-wide evaluations of antenna selection techniques

Proceedings of the Mobile Satellite Conference

A satellite-based mobile communications system provides voice and data communications to mobile users over a vast geographic area. The technical and service characteristics of mobile satellite systems (MSSs) are presented and form an in-depth view of the current MSS status at the system and subsystem levels. Major emphasis is placed on developments, current and future, in the following critical MSS technology areas: vehicle antennas, networking, modulation and coding, speech compression, channel characterization, space segment technology and MSS experiments. Also, the mobile satellite communications needs of government agencies are addressed, as is the MSS potential to fulfill them