In modern wireless communication systems, radio propagation modeling to estimate pathloss has always been a fundamental task in system design and optimization. The state-of-the-art empirical propagation models are based on measurements in specific environments and limited in their ability to capture idiosyncrasies of various propagation environments. To cope with this problem, ray-tracing based solutions are used in commercial planning tools, but they tend to be extremely time-consuming and expensive. We propose a Machine Learning (ML)-based model that leverages novel key predictors for estimating pathloss. By quantitatively evaluating the ability of various ML algorithms in terms of predictive, generalization and computational performance, our results show that Light Gradient Boosting Machine (LightGBM) algorithm overall outperforms others, even with sparse training data, by providing a 65% increase in prediction accuracy as compared to empirical models and 13x decrease in prediction time as compared to ray-tracing. To address the interpretability challenge that thwarts the adoption of most ML-based models, we perform extensive secondary analysis using SHapley Additive exPlanations (SHAP) method, yielding many practically useful insights that can be leveraged for intelligently tuning the network configuration, selective enrichment of training data in real networks and for building lighter ML-based propagation model to enable low-latency use-cases.

In the wake of network densification and multi-band operation in emerging cellular networks, mobility and handover management is becoming a major bottleneck. The problem is further aggravated by the fact that holistic mobility management solutions for different types of handovers, namely inter-frequency and intra-frequency handovers, remain scarce. This paper presents a first mobility management solution that concurrently optimizes inter-frequency related A5 parameters and intra-frequency related A3 parameters. We analyze and optimize five parameters namely A5-time to trigger (TTT), A5-threshold1, A5-threshold2, A3-TTT, and A3-offset to jointly maximize three critical key performance indicators (KPIs): edge user reference signal received power (RSRP), handover success rate (HOSR) and load between frequency bands. In the absence of tractable analytical models due to system level complexity, we leverage machine learning to quantify the KPIs as a function of the mobility parameters. An XGBoost based model has the best performance for edge RSRP and HOSR while random forest outperforms others for load prediction. An analysis of the mobility parameters provides several insights: 1) there exists a strong coupling between A3 and A5 parameters; 2) an optimal set of parameters exists for each KPI; and 3) the optimal parameters vary for different KPIs. We also perform a SHAP based sensitivity to help resolve the parametric conflict between the KPIs. Finally, we formulate a maximization problem, show it is non-convex, and solve it utilizing simulated annealing (SA). Results indicate that ML-based SA-aided solution is more than 14x faster than the brute force approach with a slight loss in optimality.

Fault diagnosis is turning out to be an intense challenge due to the increasing complexity of the emerging cellular networks. The root-cause analysis of coverage-related network anomalies is traditionally carried out by human experts. However, due to the vast complexity and the increasing cell density of the emerging cellular networks, it is neither practical nor financially viable. To address this, many studies are proposing artificial intelligence (AI)-based solutions using minimization of drive test (MDT) reports. Nowadays, the focus of existing studies is either on diagnosing faults in a single base station (BS) only or diagnosing a single fault in multiple BS scenarios. Moreover, they do not take into account training data sparsity (varying user equipment (UE) densities). Inspired by the emergence of convolutional neural networks (CNN), in this paper, we propose a framework combining CNN and image inpainting techniques for root-cause analysis of multiple faults in multiple base stations in the network that is robust to the sparse MDT reports, BS locations and types of faults. The results demonstrate that the proposed solution outperforms several other machine learning models on highly sparse UE density training data, which makes it a robust and scalable solution for self-healing in a real cellular network.

Densification and multi-band operation in 5G and beyond pose an unprecedented challenge for mobility management, particularly for inter-frequency handovers. The challenge is aggravated by the fact that the impact of key inter-frequency mobility parameters, namely A5 time to trigger (TTT), A5 threshold1 and A5 threshold2 on the system's performance is not fully understood. These parameters are fixed to a gold standard value or adjusted through hit and trial. This paper presents a first study to analyze and optimize A5 parameters for jointly maximizing two key performance indicators (KPIs): Reference signal received power (RSRP) and handover success rate (HOSR). As analytical modeling cannot capture the system-level complexity, a data driven approach is used. By developing XGBoost based model, that outperforms other models in terms of accuracy, we first analyze the concurrent impact of the three parameters on the two KPIs. The results reveal three key insights: 1) there exist optimal parameter values for each KPI; 2) these optimal values do not necessarily belong to the current gold standard; 3) the optimal parameter values for the two KPIs do not overlap. We then leverage the Sobol variance-based sensitivity analysis to draw some insights which can be used to avoid the parametric conflict while jointly maximizing both KPIs. We formulate the joint RSRP and HOSR optimization problem, show that it is non-convex and solve it using the genetic algorithm (GA). Comparison with the brute force-based results show that the proposed data driven GA-aided solution is 48x faster with negligible loss in optimality.

In the first phase of 5G network deployment, User Equipment (UE) will camp traditionally on LTE network. Later on, if the UE requests a 5G service, it will be made to camp simultaneously on LTE and 5G. This dual-camping is enabled through a 3GPP-standardized approach known as E-UTRAN New-Radio Dual-Connectivity (EN-DC). Unlike single-network-camping, where poor RF conditions of only one network affect user Quality-of-Experience (QoE), in EN-DC, poor RF condition in either LTE or 5G network can be detrimental to user QoE. Sub-optimal parameter configuration to activate EN-DC can hamper retainability KPI as UE may observe increased radio link failure (RLF). While the need to maximize the EN-DC activation is obvious for 5G network maximum utility, RLF avoidance is equally important to maintain the QoE requirements. We address this problem by first using Tomek Link to counter data imbalance problem and then building an AI model to predict RLF from real network low level measurements. We then propose and evaluate an RLF risk-aware EN-DC activation scheme that draws on insights from the developed RLF prediction model. Simulation using a 3GPP-compliant 5G simulator show that compared to no-conditioning on EN-DC activation, in the evaluated cell cluster, the proposed scheme can help reduce the potential RLF instances by 99%. This RLF reduction happens at the cost of 50% reduction in EN-DC activation. This is first study to present a framework and insights for operators to optimally conFigure the EN-DC activation parameters to achieve desired trade-off between maximizing 5G sites utility and QoE.

Abstract In this paper, the interplay between cooperative device‐to‐device (D2D) communications and green cellular communications in the long term evolution (LTE) and LTE‐advanced (LTE‐A) cellular systems is investigated. An efficient approach for grouping mobile terminals (MTs) into cooperative clusters is described. In each cluster, MTs cooperate via D2D communications to share content of common interest. In addition, an energy‐efficient approach for putting base stations in sleep mode in an LTE‐A heterogeneous network is presented. Finally, both methods are combined in order to ensure green communications for both the users' MTs and the operator's base stations. The presented techniques are investigated in the framework of orthogonal frequency division multiple access‐based state‐of‐the‐art LTE cellular networks, while taking resource allocation and intercell interference into account. Results show that the proposed approach leads to energy savings for both the operator and the MTs, while leading to enhanced quality of service for mobile users. Copyright © 2014 John Wiley & Sons, Ltd.

The number of vehicles on roads keeps increasing continuously, making the management of traffic flow, especially in big cities more and more challenging. One of the key enablers for having smooth traffic flows and better mobility is to rely on real-time traffic monitoring systems. These systems allow road operators to implement intelligent traffic management strategies such as the dynamic adjustment of timing and phasing of traffic lights and the adaptive road congestion charging. Moreover, better informed travelers will plan smartly their journeys and hence potentially contribute in reducing traffic jams. Traditional real-time traffic monitoring usually get real-time data from GPS-equipped fleets and fixed sensors installed in specific locations. In this paper, a new real-time traffic monitoring based on emerging vehicular communication systems is proposed. The system enables traffic monitoring with higher reliability, accuracy, and granularity. The cluster-based V2X traffic data collection mechanism is able to gather more than 99% of the available data and reduce the overhead to one quarter when compared to other approaches.

This paper presents a novel framework for joint self-optimization of backhaul as well as coverage links spectral efficiency in relay enhanced heterogeneous networks. Considering a realistic heterogeneous network deployment, where some cells contain Relay Station (RS), while others do not, we develop an analytical framework for self-optimisation of macrocell Base Station (BS) antenna tilts. Our framework exploits a unique system level perspective to enable dynamic maximization of system-wide spectral efficiency of the BS-RS backhaul links as well as that of the BS-user coverage links. A distributed and practical self-organising solution is obtained by decomposing the large scale system-wide optimization problem into local small scale optimization problems, by mimicking the operational principles of self-organisation in biological systems. The local problems are non-convex but have very small scale and can be solved via appropriate numerical methods, such as sequential quadratic programming. The performance of developed solution is evaluated through extensive system level simulations for LTE-A type networks and compared against conventional tilting benchmarks. Numerical results show that up to 50% gain in average spectral efficiency is achievable through the proposed solution depending on users geographical distributions.

Automatic detection of cells which are in outage has been identified as one of the key use cases for Self Organizing Networks (SON) for emerging and future generations of cellular systems. A special case of cell outage, referred to as Sleeping Cell (SC) remains particularly challenging to detect in state of the art SON because in this case cell goes into outage or may perform poorly without triggering an alarm for Operation and Maintenance (O&M) entity. Consequently, no SON compensation function can be launched unless SC situation is detected via drive tests or through complaints registered by the affected customers. In this paper, we present a novel solution to address this problem that makes use of minimization of drive test (MDT) measurements recently standardized by 3GPP and NGMN. To overcome the processing complexity challenge, the MDT measurements are projected to a low-dimensional space using multidimensional scaling method. Then we apply state of the art k-nearest neighbor and local outlier factor based anomaly detection models together with pre-processed MDT measurements to profile the network behaviour and to detect SC. Our numerical results show that our proposed solution can automate the SC detection process with 93% accuracy.

Despite years of physical-layer research, the capacity enhancement potential of relays is limited by the additional spectrum required for Base Station (BS)-Relay Station (RS) links. This paper presents a novel distributed solution by exploiting a system level perspective instead. Building on a realistic system model with impromptu RS deployments, we develop an analytical framework for tilt optimization that can dynamically maximize spectral efficiency of both the BS-RS and BS-user links in an online manner. To obtain a distributed self-organizing solution, the large scale system-wide optimization problem is decomposed into local small scale subproblems by applying the design principles of self-organization in biological systems. The local subproblems are non-convex, but having a very small scale, can be solved via standard nonlinear optimization techniques such as sequential quadratic programming. The performance of the developed solution is evaluated through extensive simulations for an LTE-A type system and compared against a number of benchmarks including a centralized solution obtained via brute force, that also gives an upper bound to assess the optimality gap. Results show that the proposed solution can enhance average spectral efficiency by up to 50% compared to fixed tilting, with negligible signaling overheads. The key advantage of the proposed solution is its potential for autonomous and distributed implementation.

Sleep disorders, such as insomnia can seriously affect a patient's quality of life. Sleep measurements based on polysomnographic (PSG) signals and patients' questionnaires are necessary for an accurate evaluation of insomnia. Due to recent innovations in technology, it is now possible to continuously monitor a patient's sleep at home and have their sleep data sent to a remote clinical back-end system for collection and assessment. Most of the research on sleep reported in the literature mainly looks into how to automate the analysis of the sleep data and does not address the problem of the efficient and secure transmissions of the collected health data. This paper provides an experimental evaluation of communication and security protocols that can be used in inhome sleep monitoring and health care and highlights the most suitable protocol in terms of security and overhead. Design guidelines are then derived for the deployment of effective inhome patients monitoring systems.

This paper presents an analysis of link asymmetry in 5.9GHz vehicular communication by means of on-road experiments, and using a standard compliant vehicular communication platform. Similar works have been conducted in the last decades, especially by relevant industrial stakeholders, but none or only little information has been disclosed to the public. The link asymmetry may have considerable impact on the performance of the adopted communication protocols, therefore it is highly important to study such a topic and share the outcomes with the researcher community; this is one of the main motivations behind this contribution. The importance of the results is twofold: first we show that the antenna position on the car roof has a considerable impact on the communication link, and second we demonstrate that the link symmetry is not as worst as can be imagined since the experiments show that a link can still have a good symmetry up to 300 meters of distance between two connected vehicles.

In this paper, the joint operation of cooperative device-to-device (D2D) communications and green cellular communications is investigated. An efficient approach for grouping mobile terminals (MTs) into cooperative clusters is described. In each cluster, MTs cooperate via D2D communications to share content of common interest. Furthermore, an energy-efficient technique for putting BSs in sleep mode in an LTE cellular network is presented. Finally, both methods are combined in order to ensure green communications for both the users' MTs and the operator's BSs. The studied methods are investigated in the framework of OFDMA-based state-of-the-art LTE cellular networks, while taking into account intercell interference and resource allocation.

In this paper, an actual deployment of a wireless sensor network is described. The purpose of the sensor network is to monitor and analyze air quality in Doha. Small scale wireless sensor stations communicate with a backend server to relay their measurements in real-time. Data stored on the server is subjected to intelligent processing and analysis in order to present it in different formats for different categories of end users. This paper describes a user friendly computation of an air quality index to disseminate the data to the general public. In addition, it describes data presentation for environmental experts using dedicated software tools, e.g. the R software system and its OpenAir package. Analysis and assessment of real measurement data is also performed in the paper.

The next generation Long Term Evolution (LTE) & LTE-Advanced cellular networks will be equipped with numerous Self-Organizing (SO) functions. These SO functions are being envisioned to be inevitable for technical as well as commercial viability of LTE/LTE-Advanced networks. Therefore, a lot of research effort is currently being channeled to the design of various SO functions. However, given the convoluted and complex interrelationships among cellular system design and operational parameters, a large number of these SO functions are highly susceptible to parametric or logical inter-dependencies. These inter-dependencies can induce various types of conflicts among them, thereby undermining the smooth and optimal network operation. Therefore, an implicit or explicit self-coordination framework is essential, not only to avoid potential objective or parametric conflicts among SO functions, but also to ensure the stable operation of wireless networks. In this paper we present such a self-coordination framework. Our framework builds on the comprehensive identification and classification of potential conflicts that are possible among the major SO functions envisioned by Third Generation Partnership Project (3GPP) so far. This classification is achieved by analyzing network topology mutation, temporal and spatial scopes, parametric dependencies, and logical relations that can affect the operation of SO functions in reality. We also outline a solution approach for a conflict-free implementation of multiple SO functions in LTE/LTE-Advanced networks. Moreover, as an example, we highlight future research challenges for optimum design of Mobility Load Balancing (MLB) and Mobility Robustness Optimisation (MRO).

In this study, we implement a green heuristic algorithm involving the base station sleeping strategy that aims to ensure energy saving for the radio access network of the 4GLTE (Fourth Generation Long Term Evolution) mobile networks. We propose an energy procurement model that takes into consideration the existence of multiple energy providers in the smart grid power system (e.g. fossil fuel and renewable energy sources, etc.) in addition to deployed photovoltaic panels in base station sites. Moreover, the analysis is based on the dynamic time variation of daily traffic and aims to maintain the network quality of service. Our simulation results show an important contribution in the reduction of CO2emissions that can be reached by optimal power allocation over the active base stations.

In this paper, performance of relay based MAC protocol for two way traffic is evaluated in non-saturated condition. In real life, non-saturation is more prevalent where nodes are mostly idle. The idea of Two Way Opportunistic-Medium Access Control (TWO-MAC) protocol is inspired from the current drive to "go green". TWO-MAC uses high data rate nodes to work as relays (by using network coding) for the low data rate nodes in two way communications. TWO-MAC results in higher throughput, lower delays and reduced energy consumption. This is due to the use of relay and network coding for two way transmission which lowers overall blocking time and contention due to faster transmission. Further, it lowers unnecessary overhead and overhearing which reduces the energy consumption. The contribution in this work is the throughput, energy and delay gains of using network coding at the relay in a realistic non-saturated network.

Relay-based multicasting for the purpose of cooperative content distribution is studied. Optimized relay selection is performed with the objective of minimizing the energy consumption or the content distribution delay within a cluster of cooperating mobiles. Two schemes are investigated. The first consists of the BS sending the data only to the relay, and the second scheme considers the scenario of threshold-based multicasting by the BS, where a relay is selected to transmit the data to the mobiles that were not able to receive the multicast data. Both schemes show significant superiority compared to the non-cooperative scenarios, in terms of energy consumption and delay reduction.

ABSTRACT Cooperative ad hoc networks for the efficient distribution of content of common interest are studied in the case of fast channel variations. Mobiles are grouped into cooperative clusters for the purpose of receiving the content with optimized energy efficiency. Data are sent to mobile terminals on a long range (LR) link, and then, the terminals exchange the content by using an appropriate short range wireless technology. When channel state information is available for the LR links, unicasting is used on the LR. When accurate channel state information is not available, threshold‐based multicasting is implemented on the LR. Energy minimization is formulated as an optimization problem for each scenario, and the optimal solutions are determined in closed form in scenarios with fast channel variations. Results show significant energy savings in the proposed schemes compared with the noncooperative case and other previous related work. Furthermore, the energy minimizing solutions are shown to lead to reduced delay in the content distribution process. Practical implementation aspects of the proposed methods are also discussed. Copyright © 2012 John Wiley & Sons, Ltd.

In this paper, an application of wireless sensor networks for leakage detection in underground water pipes is considered. A mobile sensor immersed in the water pipe is assumed to communicate with relay nodes on the ground surface, relaying its measured information to a base station for processing. A communication protocol between the relay nodes and the base station is presented. The proposed protocol is based on probabilistic reservation of transmission slots based on channel knowledge. The proposed protocol can be considered as an OFDMA extension of the reservation Aloha protocol. Simulation results show the superiority of the proposed communication approach.

During the last few years, several authors have studied the performance of many different types of channel codes for cooperative communication systems. Some of these codes include Low Density Parity Check (LDPC), Turbo and convolutional codes. Published results show that these codes effectively improve both the data rate and system performance in cooperative schemes such as the decode and forward (DF). Reed-Solomon (RS) codes are one of the most widely used channel codes in wireless communication systems today. These codes have also been adopted by several 3G standards including several digital video broadcasting (DVB) standards and also by worldwide interoperability for microwave access (WiMAX) which is based on the IEEE 802.16 standard. However, published literature shows no specific study to investigate their performance for the cooperative communication environment. Using the component codes adopted in the IEEE 802.16 standard, this paper investigates the performance of the concatenated RS coding schemes for cooperative communication. This paper first analyses the standard RS-coded DF cooperative system. The results obtained for the standard RS-coded scheme show huge gains over the non-cooperative system. Some of the problems of the standard DF relay protocol is then discussed and an improved RS-coded DF cooperative scheme is proposed. The performance of the proposed scheme shows significant gains over the standard RS-coded DF system.

This paper introduces two general relationships concerning the output signal-to-noise ratio distribution and the bit error performance of the nonideal maximal ratio combiner. The imperfections are modeled as Gaussian distributed weighting errors in the channel gain estimates used for coherent combination. The general form for the bit error rate is applicable to any modulation format.

The average bit-error rate (BER) performance of /spl pi//4-shifted differential quadrature phase shift keying (/spl pi//4-DQPSK) in the presence of multiple independent cochannel interferers in frequency-nonselective fading environments is analyzed. Nyquist shaped pulses are used and post detection diversity combining is employed at the receiver. The use of both L-branch post detection equal gain combining (EGC) and L-branch post detection selection combining (SC) are considered. Two approaches for representing the cochannel interference are investigated. These are a Gaussian interference model and a synchronous interference model. The accuracies of both of these models are assessed by comparing their BER performances with precise BER results. The precise BER results are obtained by using a combination of analysis and simulation. Attention is given, in particular, to the outdoor microcellular environment. The results of this paper indicate that the synchronous interference model may overestimate the effects of interference while the Gaussian interference model may underestimate the effects of interference.

The performance of M-ary differential phase shift keying (MDPSK) on frequency-selective slow Rayleigh fading, lognormal shadowed channels with diversity combining is analyzed for mobile and portable applications. The use of L-branch equal gain postdetection microdiversity combining to mitigate the effects of fading and P-port macrodiversity to alleviate the effects of shadowing are investigated. Four performance criteria are considered for a frequency-selective multipath fading, intersymbol interference channel. These are, the short term bit error rate (BER), the irreducible BER, the complementary distribution over the lognormal shadowing of the average BER, and the probability that the instantaneous BER exceeds a threshold value, averaged over a spatial environment. Closed-form expressions for the four performance criteria are obtained. The BER and outage performance results show that diversity combining is an effective method for improving the system performance (and hence system reliability), when the normalized delay spread is not large. It is also seen that, in most cases, 4DPSK gives the best performance followed by 8DPSK and 2DPSK, respectively, for a given information throughput.>

We investigate the effects of correlation on the performance of diversity systems in wideband wireless radio environments. Specifically, the average bit error rate (BER) performance of M-ary differential phase shift keying (MDPSK) on correlated frequency-selective slow Rayleigh fading channels is analyzed. A two-branch diversity receiver with postdetection equal gain combining is considered. Nyquist pulse shaping is used and differential detection is employed at the receiver. The effects of cochannel interference on the system performance are assessed using a Gaussian interference model. To further enhance the system performance, the effects of combined diversity and forward error correction (FEC) coding on the average BER are investigated. Results using short cyclic block codes with perfect bit interleaving are obtained. The effects of the root mean square (RMS) delay spread, the amount of correlation, and the level of modulation, M, on the average BER are investigated in detail for both coded and uncoded systems. The results show that dual branch diversity combining with a correlation coefficient of 0.5 outperforms (in terms of BER) short block codes with perfect bit interleaving, and that combined diversity and coding strategies are effective in combatting the effects of frequency-selective fading.

The performances of QPSK in the presence of cochannel interference in both nonfading and fading environments are analyzed. Three approaches for representing the cochannel interference are investigated. These are a precise error probability method, a sum of sinusoids (sinusoidal) model, and a Gaussian interference model. In addition to determining precise results for the performance of QPSK in cochannel interference, we examine the validity of these two interference models in both additive white Gaussian noise (AWGN) environments and in different flat fading environments; Rayleigh, Ricean, and Nakagami. Nyquist pulse shaping is considered and the effects of cross channel ISI produced by the cochannel interference are accounted for in the precise interference model. Also accounted for are the random symbol and carrier timing offsets of the interfering signals. Two performance criteria are considered. These are the average bit error rate and the interference penalty. The latter is defined as the increase in signal-to-noise power ratio (SNR) required by a system with cochannel interference in order to maintain the same BER as a system without interference. Attention is given, in particular, to the outdoor microcellular fading environment. In this environment, the fading experienced by the interfering signals may be represented by a Rayleigh-fading model while the fading experienced by the desired signal may be represented by a Ricean or a Nakagami-fading model.>

Four methods that can be used to approximate the distribution function (DF) of a sum of independent lognormal random variables (RVs) are compared. The aim is to determine the best method to compute the DF considering both accuracy and computational effort. The investigation focuses on values of the dB spread, σ, valid for practical problems in wireless transmission, where σ is between 6 dB and 12 dB. Contrary to some previous reports, our results show that the simpler Wilkinson's approach gives a more accurate estimate, in some cases of interest, than Schwartz and Yeh's 1982 approach.

Several approaches that can be used to compute the distribution of a sum of correlated lognormal random variables (RVs) are investigated. The aim is to determine which method is best for computing the complementary distribution function (CDF) of a sum of correlated lognormal RVs considering both accuracy and computational effort. Then, using these techniques, we compute the outage probability of a desired lognormal shadowed signal in the presence of multiple correlated lognormal cochannel interferers. The outage results are presented as a function of the reuse factor. Simulation results are used for verification and comparison. Overall, the results obtained in this paper show that among the three methods considered in this paper Wilkinson's approach may be the best method to compute tire CDF of sums of correlated lognormal RVs (and hence the outage probability in correlated lognormal shadowed mobile radio environments). This is due to both its accuracy and computational simplicity over the range of parameters valid for practical applications.>

The performance of M-ary differential phase shift keying (MDPSK) with diversity combining in frequency-selective slow Ricean fading with and without cochannel interference has been analyzed. The use of L-branch post-detection equal gain diversity combining to mitigate the effects of fading has been investigated. Expressions for the average BER were derived with and without cochannel interference. For the case of cochannel interference, precise average BER results were obtained by using a combination of analysis and simulation. Results obtained using a Gaussian interference model were also obtained. The accuracy of the Gaussian model was assessed by comparing its average BER performance with precise average BER results. The comparative performances of 2DPSK, 4DPSK, and 8DPSK have shown the following. For the same information throughput, it was seen that for small values of the Ricean K-factor (K=0 dB), the best BER performance is obtained in most cases by using 4DPSK. For large values of the Ricean K-factor (K=7 dB), it was seen that the best BER performance in most cases is obtained by using 2DPSK. The results in the paper have also shown that the Gaussian interference model can give an excellent approximation to the precise interference model for the case of no diversity (L=l). For the case of 2-branch postdetection EG combining, it was seen that the Gaussian model gives a good approximation to the precise model for small to medium values of SNR and may underestimate the effects of interference for large values of SNR.>

-The performance of an L-branch equal gain (EG) combiner on slow and nonselective Rician fading channels is analyzed. Two performance criteria are considered; the probability distribution of signal-to-noise power ratio (SNR) at the output of the EG combiner and the average bit error rate (BER). Matched filter receivers are considered for two binary modulation formats, coherent phase shift keying (NCFSK). Results using both maximal ratio combing (MRC) and selection diversity combining (SC) are presented for comparison. Our results show that from a feasibility and practical tradeoffs point of view, the performance of an EG combiner may be a good as that of a MR combiner. The effects of gain unbalance between branches of the EG combiner on the probability distribution of SNR and on the bit error rates are also investigated.

The improvements achievable using diversity with matched filter NCFSK (and DPSK) receivers operating on log-normal shadowed Nakagami-fading channels are analyzed. Three microdiversity techniques, equal gain combining (EGC), maximal ratio combining (MRC) and selection combining (SC) are compared. The system performances are assessed by considering two measures of coverage; one well suited for mobile users and one well suited for portable users. The detrimental effects of multipath fading in cellular mobile radio systems can be mitigated by using a number of microdiversity paths at the receiver. The effects of shadowing can be mitigated by using a number K of macrodiversity radio ports to serve each cell. The improvements gained by using microdiversity to combat multipath fading and macrodiversity to combat shadowing are investigated. The effects of the fading severity, the number of microdiversity branches at each port L and the number of macrodiversity ports K on the system performance are investigated in detail. The results, in most cases, are obtained by carrying out a single numerical integration (for any order of diversity). The results show that although MRC gives the best performance, EGC and SC perform nearly as well for dual (L=2) diversity. For larger L, i.e., L/spl ges/4, the relative performance of SC deteriorates substantially whereas the performance of EGC remains close to that of MRC. Also, our results show that as the fading gets less severe, the performance of EGC gets closer to that of MRC, while the performance of SC worsens compared to that of MRC.>

The performances of switched diversity systems operating on generalized (Nakagami)-fading channels are analyzed using a discrete-time model. The average bit error rate (BER) of binary noncoherent frequency shift keying (NCFSK) on slow, nonselective Nakagami-fading channels is derived. Closed-form expressions that can be used to determine optimum switching thresholds (in a minimum error rate sense) are also derived. In addition, the use of optimum fixed thresholds is considered. It is found that a considerable amount of diversity gain can be obtained using an optimum fixed (rather than adaptive) switching threshold. Results are obtained for both independent and correlated Nakagami-fading branch signals. The effects of fading severity and the correlation coefficient on both the BER and on the optimum switching threshold are investigated. It is shown that useful diversity gain can be obtained with power correlation coefficients as high as 0.9 when the fading is strong. The results for a Rayleigh channel are obtained and presented as a special case of generalized-fading model.>

Channels having large low-frequency attenuation are of much interest. Low-frequency removal may result from transformer or capacitor coupling. Examples include ISDN loop transmission (transformer coupling) and wireless systems (capacitor coupled amplifiers). Despite this interest, few works have explicitly examined the problem of calculating the average probability of error for these systems, in which the intersymbol interference from a single pulse may extend over hundreds or even thousands of symbols. Efficient series techniques for evaluation of the error probabilities of multilevel pulse amplitude modulations and multilevel duobinary signaling are derived. The method is applicable to any additive noise possessing an even probability density function. The Gaussian noise case is examined in detail. Examples of Nyquist I signaling and suboptimal detection of nonreturn-to-zero pulse codes are considered. The results are compared to previous published results. It is seen that an often cited upper bound, though within a factor of about ten in error probability for small to medium intersymbol interference conditions, may significantly overestimate the system degradation due to low-frequency attenuation when the intersymbol interference is large.>

An infinite series for the complementary probability distribution function (CDF) of the signal-to-noise ratio (SNR) at the output of L-branch equal-gain (EG) diversity combiners in Nakagami (1960) fading channels is derived. The bit error rate for a matched filter receiver is analyzed for the L-branch EG combiner and different fading parameters. Both coherent phase shift keying (CPSK) and differential coherent phase shift keying (DCPSK) are considered. The effects of gain unbalance between branches on the probability distribution of the SNR and on the bit error rates are investigated. Bit error rate results are also obtained for coherent and noncoherent reception of frequency shift keying (FSK). The effects of gain unbalances on FSK modulations are also investigated. Bit error rates for EG combining on Rayleigh fading channels are obtained for L>2. These results are presented as a special case of the more generalized Nakagami fading model.>