The growing spectrum crunch has motivated exploratory efforts in the use of LTE in the 5 GHz bands for downlink traffic. However, this paradigm raises concerns of fair sharing of the spectrum and the adverse impact of scheduled LTE frames on Wi-Fi Packet Success Rates (PSR). To address this issue, we propose E-Fi, an interference-evasion mechanism that allows Wi-Fi devices to survive LTE transmissions without any cooperation between these two different standards. Different from existing approaches, we argue that the simple use of Almost Blank Subframes (ABS) within the LTE standard offering short channel access windows overestimates opportunities for Wi-Fi. The pilots embedded in the ABS not only interfere with Wi-Fi but also adversely impact the carrier sensing function. E-Fi mitigates this problem through a two-fold approach. It uses a combination of (i) Wi-Fi Direct with packet relaying and (ii) classical distributed coordination function to reach distant nodes. Second, it ensures load balancing for both Wi-Fi uplink and downlink traffic with high PSR by creating node-groups based with dedicated contention-based medium access intervals. Our approach is validated by comprehensive simulation and experimental results that indicate significantly higher throughput in E-Fi compared to classical Wi-Fi.

In cognitive radio networks (CRNs), knowledge of the primary users (PUs) position can be used to avoid harmful interference to the primary network, while at the same time be exploited to improve CR performance. In this paper, a localization algorithm is developed to calculate PUs position and a novel location based CR (LCR) routing protocol is proposed that has the following properties: (i) it considers the existence of heterogeneous PUs, (ii) exploits PUs location information, (iii) jointly selects spectrum and route, (iv) protects PUs from interference. Clusters of CRs are defined according to the spectral characteristics in a given location area, and the LCR routing protocol acts in two steps: intra-cluster and inter-cluster. Simulations are conducted in terms of CR end-to-end performance and PUs collision risk. Results reveal the importance of formulating routing protocol in terms of PU protection, which is a unique features in CR networks.

In this paper, a novel Cognitive Radio Resource Management (RRM) is proposed to improve the spectrum utilization efficiency. In this system, heterogeneous Primary Users (PUs) with multiple features are considered where these PU features are exploited to improve the adaptability in Cognitive Radio (CR) networks and, thus, to design an efficient Cognitive RRM. An optimization framework is developed by considering heterogeneous PUs and variable CR demands while assuring interference protection towards PUs. A suboptimal solution is proposed after showing that an optimal solution is computationally infeasible. Simulation results are conducted in terms of total achieved data rate and satisfaction of CRs requirements.

In this paper we introduce some significant improvements to a well known algorithm for multicast in overlay networks, namely ZigZag. The improvements are mainly related to a better handling of peer churn, avoiding service interruption to the subtree rooted at the departed node. Since the target is a video streaming service, additional constraints are related to a minimum serving quality for outgoing links. This translates in a maximum number of children for each node depending on its outgoing link capacity: to allow this, more realistic constraints on node heterogeneity are introduced so that the multicast tree is allowed to grow unbalanced. It is also shown that exploiting the overlapped control structure with scalable coded video it is possible to minimize service interruptions due to peers departure while minimizing signaling overhead. The changes have been implemented and validated using network simulator 2 to show the effectiveness of the procedures.

The ability of adapting to the environment in the most efficient way is a crucial issue in Cognitive Radio (CR) networks. For this purpose, an accurate estimation of the characteristics and activity of the Primary Users (PUs) is required. A system that takes into account heterogeneous PUs with several features is developed. A new scheme is integrated in the system to exploit these motleys and to improve the adaptability in CR networks. Through the proposed PU signal type recognition, the PU signal is detected and classified. The features of each PU type: the allowed interference levels, the bandwidth and the idle time, are extracted and exploited for CR adaptability effects. For this, a new CR throughput/interference adapter is proposed. The CR throughput is efficiently increased depending on the specific characteristics of PU types. Simulation results show that the proposed PU type recognition detects, distinguishes and classifies PU signals in Additive White Gaussian Noise (AWGN). It is shown that CR throughput varies with PU features for the improvement of CR adaptability.

Orthogonal frequency division multiplexing (OFDM) is a transmission technique which is robust in multipath channels. It is though sensitive to frequency errors that may be caused by several factors such as frequency offset at the local oscillator, phase noise and mobility of the receiver. These errors may destroy orthogonality among subcarriers and introduce intercarrier interference (ICI) that may be represented in the frequency domain by means of an ICI matrix. Estimation of this matrix is crucial to optimize performance. In this work we propose two iterative methods that use pilot tones in the frequency domain and converge very quickly. The first proposed method works in two steps. Initially, correlation between received signal and estimated transmitted one is used to recover the channel matrix, and then it estimates the actual transmitted data by means of MMSE. This method is shown to be very effective in AWGN channel with frequency offset at the local oscillator or in one time variant path channel. The second method represents an extension to more severe channel conditions such as multipath fading. In this case a different frequency domain OFDM channel representation is needed and a suitable scheme is implemented to recover channel and data. Simulation results show that the proposed algorithms look promising to be used in actual implementations.

In this paper an improved decision feedback equalizer (DFE) for mobile orthogonal frequency division modulation (OFDM) systems is presented. The time-varying nature of the channel, due to the Doppler effect, produces inter carrier interference (ICI) that may be counteracted by using a DFE frequency- domain OFDM symbol equalizer. The proposed algorithm is based on a recently proposed block DFE equalizer exploiting an LDLHdecomposition. The main novelty of this work is the idea to modify the backward filter in order to have a complete MMSE linear equalization before the decisions needed for the interference cancellation. Performance may be further improved by re-filtering the signal in an iterative algorithm which makes use of the proposed backward filter at the first iteration. The proposed scheme performance is evaluated by considering a mobile WiMAX IEEE 812.16e standard transceiver.

Despite the tremendous improvements in transmission techniques, bandwidth is still a scarce resource as new services are introduced and user expectations grow. For this reason, optimization algorithms are required to efficiently exploit the diversity gain intrinsic in orthogonal frequency division multiple access (OFDMA) access networks. In a multiuser packet based multiservice environment, other issues that must be addressed relate to maintain some degree of fairness and service quality constraints. In this paper we introduce some algorithms at different complexity levels to adjust channel allocation and power in a 802.16e access network mixing different real-time and non-real-time services.

Cell sectorization is a common approach used in cellular systems to increase system capacity. In this paper a novel approach to downlink spatial filtering based on clustering algorithms is proposed for UMTS-FDD cellular networks. In more details, the well known segmentation algorithm K-means is applied for grouping users in order to define the spatial beams. It is assumed that the direction of arrival of received uplink channels known at the base-station. The ability of the proposed automated scheme is evaluated by comparing the computed beams with the optimum ones obtained heuristically in a static spatial configuration of users. Furthermore, simulation results in presence of DOA measurements errors demonstrates the reliability of the presented solution.

This paper presents a joint symbol timing recovery and equalization scheme for short burst transmission formats, useful in modern wireless systems, like, for instance, time- division multiple access schemes and future wireless packet data networks. Both data aided and decision directed solutions are considered and the joint optimization performance is pursued by means of an iterative scheme which exploits a timing error function sampled at symbol rate, implemented by means of the Farrow structure for the interpolation filter. Equalization is obtained by zero forcing linear filtering, considering a baud spaced implementation. Performance is evaluated by simulating QPSK transceivers and simulations results are compared with the ideal solutions for both symbol timing recovery and zero forcing channel equalization under frequency selective multipath fading.

We analyze traffic traces obtained from measurements at the edge gateway of the campus network of the University of Pavia. These traces have been obtained simply using the tcpdump utility and then analyzed and modeled using two different approaches. The first is based: on a hidden Markov model (HMM) the other on a stochastic generator based on a chaotic attractor. It is shown that the HMM is capable of capturing the general statistics of the observed streams despite poor long term correlation characteristics, while the chaotic model can achieve somewhat better results in long term characteristics and somewhat worse in short term. Moreover, the chaotic model is sensitive to the parameter extraction procedure.

The behavior of IP based network traffic has been the subject of several works. In this paper, we compare two modeling approaches and their ability to capture two basic traffic features: packet size distribution and interarrival times. Data traces were measured at the border gateway of the campus network of the University of Pavia at different times of the day. The two modeling schemes use respectively well established hidden Markov model (HMM) techniques and a stochastic engine derived from chaotic attractors.

Equalization of ISI is usually performed in the time domain. In fact it is difficult to operate in the frequency domain, since with the usual spectral techniques based on the Fourier transform, correspondence between temporal and frequency components is lost in the transformation. In this paper we present an application of the wavelet transform that exploits the joint time-frequency representation of this transform to equalize channels affected by ISI. It is shown that using the description of wavelets as filters, and exploiting the multispectral decomposition of the received signal, ISI can be dramatically reduced.

The paper relates to some developments in modeling attenuation time series, measured on Ka band satellite links during rain events, by means of sample generators using chaotic dynamical systems. Weighted sums of Lorenz strange attractors are first used to model target sequences by themselves ("global approach"), improving procedures already introduced. Then, similar generators are used to model only low-pass versions of the same sequences, while hidden Markov models (HMM) or shaped random number series are used to mimic the complementary high-pass sequences.

Previous works have introduced models based on deterministic chaos equations, aiming to simulate transmission processes over mobile radio digital channels at the level of the post detection error stochastic process and to reproduce their renewal or nonrenewal behaviors. In particular bursts and clusters of errors are generated by these models, exploiting the correlation between successive points sampled from the trajectories of suitable strange attractors. In this paper chaos equation models are reviewed and relevant results are discussed. Different approaches have been tested, using one or more attractors, and calling for light or heavy preprocess procedures to cope with the statistical characteristics of target gap-time series. Models derived from hidden Markov chains have been implemented to provide comparison of results. Target sequences were supplied by simulation of digital enhanced cordless telecommunications (DECT) channels or derived from reception of DECT signals by a mobile unit in indoor environments.

The MPEG-2 standard describes several options to split the video stream into sub-streams conveying information at different detail level. This fact can be exploited to generate a low quality stream with all that is necessary for a basic service, while all other sub-streams carry "detail" information to improve the quality of the reconstructed signal. In a mixed network environment, this can be exploited to allow the stream to be decoded by different terminals. Another use is to provide flexibility in tough transmission systems where either traffic or noise can give rise to severe impairments. Spatial scalability is used in a radio transmission system targeted at DVB-S (digital video broadcasting by satellite) to investigate the eventual gains. It is shown that, for a given target rate, differentiated coding can be exploited to achieve decodability and good quality at a channel SNR much lower than that of single layer streams.

The paper relates on experiments in deriving models for satellite link channels in the Ka band using nonlinear deterministic chaos equations. The trajectories of Lorenz attractors are sampled at suitable time rates and combined to obtain attenuation samples of the fading channel, following procedures suggested by previous experience in modeling the behavior of time error series in digital communication channels. Optimization cost function structures are discussed.

The work presented in this article describes a tool for object tracking, notes insertion, and information retrieval, applicable to MPEG-2 sequences. Maximum compliance with the MPEG standard is sought, so the added information is transmitted as side information without affecting the actual video-audio stream as defined in the MPEG-2 standard. Additional processing is added to a standard sequence, allowing for automatic tracking of one object across different groups of pictures. Results show that the proposed algorithm is capable of tracking objects with a good degree of precision. Features are included to alert the human operator when objects disappear, or must be considered lost, due to an excessive change in their shape.

Source modelling is one of the fundamental issues in studying the performance of networks under different traffic conditions. Previously, emphasis has been put on modelling the output of digital video sources to determine the actual load and its temporal correlation. In this paper we propose a new modelling approach based on the use of chaotic equations to generate simulated MPEG sequences. The performances of an ATM node carrying video traffic are observed using both "real" and "chaotic" input video sources. We show that the proposed model is accurate enough to capture the loss-delay characteristics of the node and can thus be used as an alternative to traditional probabilistic models.

Applications of clustering and neural network techniques to channel equalization have revealed the classification nature of this problem. This paper illustrates an implementation of a global system for mobile communications (GSM) receiver in which channel equalization and demodulation are realized by means of the nearest neighbor (NN) classifier algorithm. The most important advantage in using such techniques is the significant reduction in terms of the computational complexity compared with the maximum likelihood sequence estimation (MLSE) equalizer. The proposed approach involves symbol-by-symbol interpretation and the knowledge of the channel is embedded in the mapping process of the received symbols over the symbols of the training sequence. This means that no explicit channel estimation need be carried out, either with correlative blocks or using neural networks thus speeding up the entire process. The performance of the proposed receiver, evaluated through a channel simulator for mobile radio communications, is compared with the results obtained by means of a 16-state Viterbi algorithm and other suboptimal receivers. It is shown that the presented algorithm increases the bit error rate (BER) compared with the MLSE demodulator, but the performance degradation, despite the simplicity of the receiver, is kept within the limits imposed by the GSM specifications.

This paper studies the problems related to the transmission of digital data in ATM-like format over a noisy wireless channel affected by burst of errors. A cell structure more suitable for wireless application is proposed and a protocol for error control and packet re-transmission is presented that provides good throughput performances. This protocol is based on an ARQ scheme with partial re-transmission used in conjunction with a cyclic error detection code. The system parameters are tuned to provide easy conversion between the standard ATM cell and the wireless-ATM one.