QoS-Constrained Traffic Engineering for Interference-affected Wireless Mesh Networks with Network Coding

This thesis focuses on the QoS-constrained Traffic Engineering (TE) of Wireless Mesh Networks (WMNs) affected by Multiple Access Interference (MAI). The goal is to develop a tool for the optimization of network/physical resource allocation that enable to design WMNs supporting multicast multimedia sessions with different Quality of Service (QoS) requirements when intra-session Network Coding (NC), besides routing, can be performed at the network nodes. A wide-applicability integrated framework is proposed, that allows to jointly optimize session utilities, flow control, QoS differentiation, intra-session network coding, Media Access Control (MAC) design and power control. To cope with the nonconvex nature of the resulting cross-layer optimization problem, this thesis proposes a two-level decomposition that provides the means to attain the optimal solution through suitably designed convex subproblems. Sufficient conditions for the feasibility of the primary (nonconvex) problem and for the equivalence to its related (convex) version are derived. Furthermore, a general procedure to devise simple polyhedral outer-bounds of the capacity region, which will be shown to have a key role in the decomposition, has been developed. Algorithmic implementation of the two-level decomposition is discussed in both centralized and distributed approaches. Moreover, the asynchronous, iterative Distributed Resource Allocation Algorithm (DRAA), that quickly self-adapts to network time-evolutions (e.g., node failures and/or fading fluctuations), is developed. Numerical results that delve into the potential of both the proposed solution and the resource allocation algorithm, are provided. In detail, the two-level decomposition will be tested in unicast, multicast and multisource scenarios so as to show the performance gain achievable by the joint optimization with respect to the conventional solutions

Iterative multiuser resource allocation for inhome Power Line Communications

In a multiuser scenario, the bit-loading, which has proven decisive in resource optimization for Power Line Communications (PLCs), has to be coupled with channel assignment to fully exploit its potential. Unfortunately, finding the most performing combination of channel and power allocation leads to integer (or mixed) programming problems, which are known to be NP-hard. To overcome the complexity of the resulting optimization problem, in this paper we propose an iterative solution that is able to guarantee both fairness and Quality of Service (QoS) to the users when the overall power consumption of the system is bounded and each subchannel emission is limited. This solution embeds a Connection Admission Control (CAC) that allows to leave out badly-connected users that otherwise would negatively affect the comprehensive system performance. Numerical results compare the presented resource allocation with the common greedy-based single user approach. © 2011 IEEE

UltraWide Band Cognitive Pulse Shaping under Physical-Layer QoS Constraints

Ultra Wide Band (UWB) communication systems operate in the frequency range between 0 and 10.6 GHz so they induce the Scientific Community to solve the problem of coexistence with concurrent telecommunication services. This is the leading reason why both the Federal Communications Commission (FCC) and the European Telecommunications Standards Institute (ETSI) gave strict indications about the spectral limits to be respected and require the transmitter and receiver to be compliant with these spectral masks. To this end, it is mandatory to carefully shape the UWB pulse, for this can be accurately designed so as to avoid severe performance reduction while guarding inter-systems coexistence. The UWB technology and, more, the pulse shaping allow to apply the cognitive paradigm where the transmitter and receiver are the actors of this functionality since the performance are tied to channel features and interference presence. The widespread choice of Gaussian-like pulses has proven, however, largely suboptimal from a power emission point of view since they fail to optimize performance. Goal of this contribution is to show how to achieve a good compromise between spectral emission, rate and synchronization errors robustness, via a modified version of the Parks-McClellan method, considering channel impairments due to its frequency-selective nature and to the inter-pulse interference

Interference Management for Multiple Multicasts with Joint Distributed Source/Channel/Network Coding

This paper focuses on the QoS-constrained jointly optimal adaptive distributed source coding, channel coding, network coding and power control for Co-Channel Interference (CCI)-limited wireless multiple class multicast networks, such as, for example, Wireless Sensor Networks (WSNs). The goal is to allocate the available system-wide resources by jointly performing Loss-Less Distributed Source Coding (LLDSC) and Intra-Session Network Coding (ISNC), while leveraging channel coding and power control for CCI-mitigation. Due to the presence of CCI, the resulting cross-layer optimization problem is inherently nonconvex. Hence, we develop a distributed, iterative and asynchronous algorithm for the optimal adaptive QoS management of the available bandwidth/power/flow resources. Actual performance and adaptive capability of the proposed resource management algorithm in the presence of: i) abrupt changes of the statistics of the source flows; ii) failures of the interior network nodes; and, iii) fast fading, are numerically tested

Traffic Engineering for wireless connectionless access networks supporting QoS-demanding media applications

This paper focuses on the problem of optimal QoS Traffic Engineering (TE) in Co-Channel Interference (CCI)-affected power-limited wireless access networks that support connectionless services. By exploiting the analytical tool offered by nonlinear optimization and following the emerging "Decomposition as Optimization" paradigm [1], the approach pursued in this paper allows to develop a resource allocation algorithm that is distributed, asynchronous, scalable and self-adaptive. Interestingly, the proposed algorithm enables each node of the network to distribute its outgoing traffic among all feasible next-hops in an optimal way, as measured by an assigned global cost function of general form. This optimal traffic distribution complies with several subjective as well as objective QoS requirements advanced by the supported media flows and involves only minimum information exchange between neighboring nodes. Furthermore, it allows for load-balanced multiple forwarding paths and it is able to self-perform optimal traffic re-distribution (i.e., re-routing) in the case of failure of the underlying wireless links. Finally, actual effectiveness of the overall proposed algorithm is numerically tested via performance comparisons against both DSDV-based single-path routing algorithms and interference-aware multipath routing algorithms. © 2011 Elsevier B.V. All rights reserved

Jointly Optimal Congestion Control, Network Coding and Power Control for QoS Multicast over DiffServ MAI-affected Wireless Networks

Abstract — Recent advancements in network coding have shown great potential for efficient information multicasting in wireless packet networks in terms of both throughput and robustness. In this paper, we address the jointly optimal congestion control, network coding and self-adaptive distributed power control for DiffServ-based wireless networks. The target is to provide Quality of Service (QoS) support to multiple multicast multimedia sessions in the presence of Multiple Access Interference (MAI). To cope with the nonconvex nature of the addressed cross-layer optimization problem, we develop a two-level decomposition that is able to find the optimal solution by means of a suitable relaxed convex version of its comprising subproblems. Sufficient conditions for the equivalence of the primary (nonconvex) problem and its related (convex) version are provided, and a distributed, iterative algorithm for computing the solution of the resource allocation problem is developed. Actual performance and robustness against node-failures are numerically tested and compared with the ones of Dens

Power-Constrained Physical-Layer Goodput Maximization for Broadband Power Line Communication Links

Power Line Communication (PLC) systems are currently envisioned as a possible solution for distributing multimedia contents and allowing Internet access with a capillary (already built) network without demanding further infrastructure. The real challenge for PLCs consists in providing connectivity where Public Switch Telephone Network (PSTN)-based Internet Access and/or Wi-Fi/WiMAX seem to be unable to solve the problem of Digital Divide. In this paper we introduce a new metric, i.e. the goodput, to balance transmission rate and bit error rate (BER) in resource allocation issues for Power Line Communication systems. In detail, we state the well-known integer bit-loading problem as a goodput maximization with constraints on the power consumption and the maximum decoding time. The use of Trellis Coded Modulation (TCM) allows to pursue the goodput maximization weighing error probability and transmission rate which would have otherwise been in trade-off. Numerical results are presented to stress how our solution improves system performances, both in ideal conditions and with additional impairments such as crosstalk and impulsive noise, with respect to the conventional Maximum Rate (MR) and Minimum BER (MB) approaches and to validate the suitability of TCMs in comparison with higher complexity codes

Optimal Self-Adaptive QoS Resource Management in Interference-Affected Multicast Wireless Networks

In this paper, we focus on the quality-of-service (QoS)-constrained jointly optimal congestion control, network coding, and adaptive distributed power control for connectionless wireless networks affected by multiple access interference (MAI). The goal is to manage the available network resources, so as to support multiple multicast sessions with QoS requirements when intrasession network coding (NC) is allowed. To cope with the nonconvex nature of the resulting cross-layer optimization problem, we propose a two-level decomposition that provides the means to attain the optimal solution through suitable relaxed convex versions of its comprising subproblems. Sufficient conditions for the equivalence of the primary nonconvex problem and its related convex version are derived, occurrence of such conditions investigated, and performance with respect to conventional routing-based layered solutions analyzed. Moreover, we develop a distributed algorithm to compute the actual solution of the resource allocation problem that quickly adapts to network time-evolutions. Performance of this algorithm and its adaptivity are evaluated in the presence of varying network/fading conditions and noisy measurements