This paper aims to offer the results of the analysis of 3G mobile network usage in terms of traffic based on the case of dominant mobile operator in Bosnia and Herzegovina (B&H). By this it is identified whether the demand for more radio spectrum is legitimate. In order to satisfy the requirement for extension of radio spectrum aimed for broadband services the broadcast spectrum (470 - 700 MHz) has been investigated. The rest of the UHF broadcast band (700 - 860 MHz) was not considered since it is specified as the Digital Dividend and hence was not a subject of dynamic access to the spectrum investigation. In addition the "white space" in the TV broadcasting UHF band has been considered as one of the opportunities and challenges for the wireless access network operators. All results have been compared to the relevant researches conducted in some European, US, Asian and African countries. Ultimately the analysis results would help the modernization and enhancement of spectrum management proposing the concept of spectrum sharing and dynamic spectrum access to the national regulatory authority in B&H.

In this paper, the state-of-the-art laboratory environment is presented that is aimed for experimental verification of the earlier obtained analytical OFDM error floor model but now in concrete LTE FDD downlink channel conditions, which are for this purpose hardware and software simulated in the Communications Systems Laboratory of the University of Dubrovnik. At this point, the very preliminary verification of the earlier derived error floor formula is reported as the test results achieved by means of the industry-standard simulation tool closely match the ones coming out of the earlier model-specific basic Monte-Carlo simulations.

In this paper, we propose a model for estimating the error floor in a small-time-dispersion environment - typically indoor, where both channel and overall OFDM symbol are represented stochastically. The developed novel model for the error floor prediction involves modified common channel time dispersion parameters as well as the ones characterizing the OFDM signal. The validity of the model was confirmed by the results of the corresponding Monte-Carlo simulations.

This chapter treats performances of Maximal-Ratio Combiner (MRC) in presence of two general fading distributions, the κ-μ distribution and the η-μ distribution (Yacoub, 2007.). Namely, performances of Maximal-Ratio Combiner in fading channels have been of interest for a long time, which can be seen by a numerous publications concerning this topic. Most of these papers are concerned by Rayleigh, Nakagami-m, Hoyt (Nakagami-q), Rice (Nakagamin) and Weibull fading (Kim et al., 2003), (Annamalai et al., 2002), (da Costa et al., 2005), (Fraidenraich et al., a, 2005), and (Fraidenraich et al., b, 2005). Beside MRC, performances of selection combining, equal-gain combining, hybrid combining and switched combining in fading channels have also been studied. Most of the papers treating diversity combining have examined only dual-branch combining because of the inability to obtain closed-form expressions for evaluated parameters of diversity system. Scenarios of correlated fading in combiner’s branches have also been examined in numerous papers. Nevertheless, depending on system used and combiner’s implementation, one must take care of resources available at the receiver, such as: space, frequency, complexity, etc. Moreover, fading statistic doesn't necessary have to be the same in each branch, e.g. probability density function (PDF) can be the same, but with different parameters (Nakagami-m fading in i-th and j-th branches, with mi≠mj), or probability density functions (PDF) in different branches are different (Nakagami-m fading in i-th branch, and Rice fading in j-th branch). This chapter treats MRC outage performances in presence of κ-μ and η-μ distributed fading (Milisic et al., a, 2008), (Milisic et al., b, 2008), (Milisic et al., a, 2009) and (Milisic et al., b, 2009). This types of fading have been chosen because they include, as special cases, Nakagami-m and Nakagami-n (Rice) fading, and their entire special cases as well (e.g. Rayleigh and one-sided Gaussian fading). It will be shown that the sum of κ-μ squares is a κ-μ square as well (but with different parameters), which is an ideal choice for MRC analysis. This also applies to η-μ distribution. Throughout this chapter probability of outage and average symbol error rate, at the L-branch Maximal-Ratio Combiner’s output, will be analyzed. Chapter will be organized as follows. In the first part of the chapter we will present κ-μ and η-μ distributions, their importance, physical models, derivation of the probability density function, and relationships to other commonly used distributions. Namely, these distributions are fully characterized in terms of

Maximal-Ratio Combiner (MRC) performances in fading channels have been of interest for a long time, which can be seen by a number of papers concerning this topic. Most of these papers treat Rayleigh, Nakagami-m, Hoyt, Rice or Weibull fading. This paper treats symbol error probability (SEP) performances of MRC in presence of generalized eta-mu fading. In this paper, we will present eta-mu fading model, and expressions for SEP of the L-branch MRC output. SEP will be treated for a broad class of modulation types and for non-coherent type of detection. SEP performances of the MRC will be presented via Monte Carlo simulations and theoretical expressions.

Maximal-ratio combiner (MRC) performances in fading channels have been of interest for a long time, which can be seen by a number of papers concerning this topic. In this paper we treat bit error probability (BEP), symbol error probability (SEP) and outage probability of MRC in presence of 𝜅-𝜇 fading. We will present 𝜅-𝜇 fading model, probability density function (PDF), and cumulative distribution function (CDF). We will also present PDF, CDF, and outage probability of the L-branch MRC output. BEP/SEP will be evaluated for broad class of modulation types and for coherent and noncoherent types of detection. BEP/SEP and outage performances of the MRC will be evaluated for different number of branches via Monte Carlo simulations and theoretical expressions.

Maximal-ratio combiner (MRC) performances in fading channels have been of interest for a long time, which can be seen by a number of papers concerning this topic. Most of these papers treat rayleigh, nakagami-m, hoyt, rice or Weibull fading. This paper treats outage and symbol error probability (SEP) performances of dual-branch MRC in presence of generalized kappa - mu fading. In this paper, we will present kappa - mu. fading model, expressions for outage and SEP of the L-branch MRC output, but we will only hold on to the most interesting case when L=2. SEP will be treated for a broad class of modulation types and for coherent and non-coherent types of detection. Outage and SEP performances of the MRC will be presented via Monte Carlo simulations and theoretical expressions.

Maximal-Ratio combiner (MRC) performances in fading channels have been of interest for a long time, which can be seen by a number of papers concerning this topic. Most of these papers treat Rayleigh, Nakagami-m, Hoyt, Rice or Weibull fading. This paper treats outage performances of MRC in presence of generalized kappa- mu fading. In this paper, we will present kappa- mu fading model, probability density function (PDF), cumulative distribution function (CDF), expression for n-th order moment and outage probability. We will also present PDF, CDF and outage probability of the L-branch MRC output. Outage performances of the MRC will be presented for different number of branches via Monte Carlo simulations and theoretical expressions.

Recently, papers have appeared treating channels in presence of composite fading. Due to composite fading PDF complexity, gamma shadowing distribution instead of lognormal is proposed, to simplify analytical expressions. In order to estimate cell coverage in recent papers, only shadow fading model subdued to lognormal distribution was observed. In this paper, both mentioned models for cell coverage estimation are treated and compared: model with lognormal shadowing and model based on shadow fading which is subdued to gamma distribution (gamma shadowing). The impact of multipath fading, as part of path loss has been analyzed and expressed through composite fading model (Nakagami-m multipath/Gamma shadow fading). For all these models analytical closed forms for reliability parameters are derived (cell edge reliability and cell area reliability). Based on these results, reliability parameters in gamma shadowing and composite fading models are compared to a model which respects presence of lognormal shadowing, and presented in graphs. Also a simulation in order to compare different shadowing models and their impact on actual cell coverage has been made. In order to analyze signal coverage, cell radius estimation has been chose as relevant parameter for coverage verification and the effects of limited number of measured strength samples on cell radius estimation, using both proposed distributions, has been analyzed.