Reducing the number of users serviced by congested cellular towers given an offered load and a minimum level of acceptable user quality is a major challenge in the operation of LTE networks. In this paper, we utilize a supervised Deep Learning (DL) technique to predict the LTE and LTE-A loading of connected users and then dynamically predict the congestion threshold of each cellular tower under offered load. We then use the predicted congestion thresholds together with quality constraints to fine-tune cellular network operating parameters leading to minimizing overall network congestion. We propose two sets of optimization algorithms to solve our formulated congestion optimization problem. Those are, namely, a variant of Simulated Annealing (SA) algorithm to which we refer as Block Coordinated Descent Simulated Annealing (BCDSA) and Genetic Algorithm (GA). We first compare the performance of integrated DL-BCDSA and DL-GA algorithms and then show that our integrated DL-BCDSA can outperform existing state-of-the-art commercial self organizing tool already deployed in actual cellular networks.

This work studies connectivity maintenance of mobile networks. A mobile network of interest consists of two types of nodes, pre-deployed (client) and intermediate nodes. Upon initial deployment of client nodes in a field, multiple stationary intermediate nodes are placed strategically to establish robust network connectivity. We study scenarios in which an initially connected network consisting of pre-deployed and intermediate nodes is exposed to mobility of the former. Two types of node mobility scenarios are investigated. The first scenario analyzes the bounds of mobility when pre-deployed nodes move at small scales. The bounds of node mobility preserving connectivity are derived through analysis and verified by simulations. The second scenario considers the movement of pre-deployed nodes beyond the bounds of the first scenario thereby breaking connected links and partitioning the connected network. This scenario then considers relocating the existing intermediate nodes in order to reestablish connectivity. A general formulation is proposed in the form of an optimization problem. We prove that the general formulation of the problem is NP-hard. Next, we turn our attention to a practical scenario in which the location of nodes is made available using GPS signals. We solve the problem of practical scenario in polynomial time and analyze the complexity of our solution. We also present comprehensive performance evaluation results of our proposed algorithm.

Every year, mobile operators spend hundreds of millions of dollars to improve their cellular capacities. Capacity improvements typically aim at adding carriers, frequency bands, radios, antenna systems, small cells, and sectors. In many cases, traffic load associated with special events push cellular sectors to their breakpoints defined as thresholds of access attempts leading to user access failures. Often times, mobile operators manually handle special events by dedicating human resources to them instead of deploying automated solutions. In this paper, we first use a pair of supervised learning approaches to model cellular network capacity measured in terms of total number of users carried as a function of user access attempts. Relying on our modeling results, we then predict the associated breakpoints of sectors as functions of user access attempts. Next, we formulate an optimization problem to maximize network capacity subject to constraints of user quality and predicted breakpoints. Among a number of alternatives, we propose a novel variant of simulated annealing referred to as Block Coordinated Descent Simulated Annealing (BCDSA) to solve the problem. Our performance measurements show that BCDSA offers dramatically improved algorithmic success rates as well as the best utility, runtime, and confidence range characteristics compared to alternative solutions.

In this paper, an optimal link selection and data rate assignment algorithm for spatial time division multiple access (STDMA) medium access control (MAC) protocols is exploited. The motivation for this study is jointly searching for optimal links and corresponding rates in simultaneous transmission environments in order to maximize the throughput capacity in each time slot. A mathematical formulation for exploring such links and rates combination under power and delay constrains is developed. Then, we transform this formulation into a standard knapsack problem (KP). Finally, we solve this KP using discrete dynamic programming (DDP) and propose a joint optimal link and rate search (JOLRS) algorithm which can be generically embedded with any existing STDMA MAC protocol. Through theoretical and experimental studies, we show that our JOLRS algorithm significantly outperforms baseline alternatives and similar existing algorithms in throughput, power consumption, and PER performance.

The problem of connectivity in heterogeneous networks constitutes an important yet challenging topic in the literature of communication networks. A heterogeneous network contains nodes with different communication radii and degrees of connectivity. This paper addresses the problem of connectivity in multi-tier heterogeneous network graphs through systematic placement of advantaged nodes. The node placement method is based on a so-called hexagonal coordinate system (HCS) in which we develop an extended algebra. Relying on the HCS, we formulate and solve a class of geometric distance optimization problems aiming at guaranteeing the connectivity of a graph of multiple clusters of nodes. We show the effectiveness of our approach through experimental results in comparison with minimum spanning tree (MST) algorithms.

Key pre-distribution algorithms have recently emerged as efficient alternatives of key management in today’s secure communications landscape. Secure routing techniques using key pre-distribution algorithms require special algorithms capable of finding optimal secure overlay paths. To the best of our knowledge, the literature of key pre-distribution systems is still facing a major void in proposing optimal overlay routing algorithms. In the literature work, traditional routing algorithms are typically used twice to find a NETWORK layer path from the source node to the destination and then to find required cryptographic paths. In this paper, we model the problem of secure routing using weighted directed graphs and propose a Boolean linear programming (LP) problem to find the optimal path. Albeit the fact that the solutions to Boolean LP problems are of much higher complexities, we propose a method for solving our problem in polynomial time. In order to evaluate its performance and security measures,we apply our proposed algorithm to a number of recently proposed symmetric and asymmetric key pre-distribution methods. The results show that our proposed algorithm offers great network performance improvements as well as security enhancements when augmenting baseline techniques.

Multihop spatial time division multiple access (STDMA) medium access control (MAC) protocols constitute an important building block of wireless networks. There are not many practical power control algorithms that can optimally tradeoff power consumption against transmission rates with a reasonable computational complexity. In this paper, we introduce an energy-efficient distributed power control algorithm for STDMA MAC protocols. The motivation for this study is two fold, namely, maximizing the spatial reuse of the system resources and maximizing power efficiency. We develop a mathematical formulation for maximizing spatial reuse and power efficiency under discrete SINR and rate constrains. After proving that power is a convex function of data rates in our problem, we demonstrate that our problem in simultaneous transmission environments can be reduced to a linear programming (LP) problem. Then, we solve this LP problem using dynamic programming (DP). Finally, based on our proposed solution, we propose a low complexity optimal power control (OPC) algorithm which can be generically embedded within any existing STDMA MAC protocol. Through analytical and experimental studies, we show that our power control algorithm cannot only significantly improve the throughput, power consumption, and delay performance of STDMA MAC protocols compared to their baseline alternatives, but also outperform existing STDMA algorithms.

In this paper, we exploit a distributed power control algorithm for spatial time division multiple access (STDMA) medium access control (MAC) protocols. Our algorithm aims at maximizing the number of simultaneous transmissions while concurrently minimizing the corresponding transmission powers in a given time slot. We formulate the problem of interest as a linear programming (LP) problem subject to discrete constraints. Then, we solve the problem using dynamic programming (DP). Based on our solution, we propose a low complexity optimal power control algorithm which can be generically embedded into any existing STDMA MAC protocol. Through analytical and experimental studies, we show that not only our power control algorithm significantly improves the throughput performance and the power consumption of STDMA MAC protocols compared to their baseline alternatives but it also outperforms the existing power control algorithms devised for STDMA MAC protocols.

The variation of bandwidth in wireless networks imposes significant challenges to the operation of congestion control protocols, especially, those relying on estimations of link bandwidth. For example, TCP CUBIC probes the end-to-end available link bandwidth while XCP and VCP require an explicit knowledge of the available link bandwidth at intermediate nodes. Thus, these protocols are subject to oscillatory behavior and serious performance deterioration in wireless networks without properly compensating against the fluctuations of the bandwidth. In this paper, we propose a bandwidth estimation scheme utilizing Extended Kalman Filtering (EKF) to which we refer as EBE. Rather than directly measuring bandwidth in real-time, EBE monitors either per flow states at a sender or persistent queue sizes to predict the available bandwidth. It is utilized to efficiently cope with bandwidth variations thereby stabilizing and improving the performance of congestion control protocols in wireless networks. We implement EBE in NS2 and integrate it with XCP, VCP, TCP CUBIC, and few other TCP variants. Through extensive simulation studies, we demonstrate significant performance improvements of these protocols in wireless networks as the result of using EBE.

Multi-user detection is an efficient approach proposed to boost the spectral efficiency of a wireless communication system. While multi-user detection in synchronous systems or in flat fading environments has been successfully addressed, it is still an open and challenging problem in the practical case of asynchronous MIMO systems employing space-frequency (time) block coding and operating in frequency selective environments. In this paper, we show how the concept of multi-user detection can be efficiently extended to the latter case with a low complexity overhead and a small performance loss compared to the synchronous case.

In this paper, we present UAV-aided Cross-Layer Routing Protocol (UCLR) that aims at improving the routing performance of a ground MANET network with aid from an Unmanned Aerial Vehicle (UAV). The UAV is added to a connected backbone formed by a collection of designated nodes in order to combat link failures and wireless link effects detected at PHY/MAC layers before the routing table adapts to the changes. In the context of the UCLR protocol, we introduce a UAV-aided cross-layer routing scheme, an associated cross-layer routing metric, and a UAV load-balancing algorithm. We implement UCLR using Linux Quagga routing suite along with OSPF MANET Designated Routing (MDR) and demonstrate its performance improvements compared to the original MDR through emulation studies.

Router Assisted congestion control Protocols (RAPs) appear to be the most efficient solutions to the TCP performance degradation issue in high Bandwidth Delay Product (BDP) networks. Global deployment of RAPs such as XCP, VCP, and MPCP however, has been challenging due to their need for router support. In this paper, we propose RAPPEP a framework for deploying RAPs on potential congestion zones such as satellite links that are locally utilizing the architecture of TCP Performance Enhancement Proxy (PEP). Such a marriage allows for an immediate deployment of RAPs without the need for global router support, while still being able to take advantage of sophisticated RAPs. Beyond the deployed congestion zone, RAPPEP is completely transparent to the rest of the network including end nodes and other routers. Adapting from two implementations of RAPs and an implementation of TCP PEP (PEPSal), we implement and integrate RAPPEP in the Linux kernel and demonstrate its performance improvement compared to PEPSal through emulation studies.

Aside from the introduction of many new schemes, the use of TCP-based AQM schemes and in specific RED is anticipated to continue in foreseeable future as the de-facto standard of network congestion control. Therefore, conducting extra research work aiming at improving the performance of RED is still a topic of high interest. In this paper, we present an analytical study aiming at the fine tuning of the RED parameters. Utilizing a statistical analysis approach, we formulate an optimization problem aimed at addressing the loss and delay tradeoff of the RED queuing discipline. We provide a two-phase iterative solution to the problem in order to identify the settings of the RED parameters. We discuss the convergence characteristics of our solution and investigate its low complexity characteristics. Through extensive NS2 experiments, we illustrate the advantages of our proposed optimization approach by comparing its results to those of adaptive RED as well as standard RED with recommended parameter settings.

The use of multiple packet reception (MPR) can alleviate congestion in multi-hop networks and improve network Goodput. However, a sophisticated design is required in order to enable MPR in such networks considering the heterogeneity of transiting packets, both in size and arrival times. In this paper, we introduce a cross-layer MPR-PHY/MAC design suitable for multi-hop ad-hoc networks. Our design identifies three phases of operation tied to the network offered load. Simulation results show that the saturation Goodput of a network using our proposed MPR-PHY/MAC design is better than that of a network using standard IEEE 802.11 PHY and MAC by a factor of at least 50%.

Relying on physical layer security is an attractive alternative of utilizing cryptographic algorithms at upper layers of protocol stack for secure communications. In this paper, we consider a two-hop wireless relay network in the presence of an eavesdropper. Our scenario of interest spans over a four-node network model including a source, a destination, a trusted relay, and an untrusted eavesdropper in which the relay forwards the source message in a decode-and-forward (DF) fashion. The source and relay are allowed to use some of their available power to transmit jamming signals in order to create interference at the eavesdropper. The relay and destination are assumed to have the knowledge of the jamming signals. An important question is how to allocate the transmission power of the message signal and that of the jamming signal. First, we propose an optimal power allocation solution in which the knowledge of global channel state information (CSI) is required. To facilitate practical system design, two simple yet sub-optimal power allocation solutions are proposed which do not rely on eavesdropper's channels. For the purpose of performance comparisons, power allocation problems for two benchmark schemes without jamming are also analyzed.

Wireless link effects impose unique challenges to routing protocols in Mobile Ad Hoc Networks (MANETs). In this paper, we propose Hybrid Cross-Layer Routing (HCLR) protocol designed and implemented based on the premise of being able to leverage a pair of proactive and reactive routing schemes. While the former is used to avoid long routing discovery latencies, the latter is used to compensate against wireless link effects thereby allowing for making more intelligent routing decisions. Compared to standalone proactive or reactive routing protocols, HCLR provides a two-tier improvement logic by performing local on-demand search in an n-hop neighborhood utilizing a 2-tuple cross-layer routing metric. We implement HCLR in Linux Quagga suite and demonstrate its performance improvements compared to OSPF MANET Designated Routing (MDR) through emulation studies.

The use of multiple-packet reception (MPR) in wireless networks is known to improve throughput especially in high-traffic conditions. The lack of synchronization among the nodes in random access systems introduces significant challenges toward the adoption of MPR in the PHY and the MAC design for systems using MPR. In this paper, we propose an asynchronous MPR method for the PHY and also design a compatible random access MAC for wireless local area networks (WLANs). Relying on space-time coding techniques, our MPR method detects multiple asynchronous packets while providing diversity and low bit error rates at the PHY layer. Extending the design of IEEE 802.11, our MPR MAC design encourages simultaneous packet transmissions and handles multiple packet receptions. Simulation results show that the throughput of a WLAN significantly improves in many scenarios of operation using our proposed PHY/MAC MPR framework.

Coping with collisions is one of the biggest challenges in the design of MAC algorithms for wireless networks. Recent advances in MIMO communications have provided the possibility of simple detection of colliding packets. In this paper, we introduce a new MIMO/MPR-aware cross-layer MAC/PHY design that is capable of combating collisions through the use of a multiple packet reception technique. Analytical and simulation results show that the proposed MAC design can considerably improve the throughput of a WLAN operating over lossy links.

The performance of prevalent wireless MAC protocols is a function of network contention level and the capabilities of the underlying network nodes. While contention-based MAC protocols such as CSMA experience significant performance degradation under high contention levels, slot-based MAC protocols such as TDMA perform in the opposite way. In this paper, we propose a hybrid MAC protocol to which we refer as Load-Adaptive MAC (LA-MAC) protocol for MANETs formed by a collection of Multiple-Input Multiple-Output (MIMO) equipped nodes. By adaptively switching its mode of operation between CSMA and TDMA, LA-MAC achieves a high channel utilization and a reasonable delay profile under both high and low contention levels identified by the measured collision rate of the MAC frames. As a cross-layer protocol, LA-MAC relies on the information received from the physical layer in order to distinguish between corrupted frames due to actual collisions as opposed to those corrupted by wireless link effects such as fading. We describe the design of LA-MAC protocol and report on its implementation in a MANET testbed formed by a collection of MIMO Universal Software Radio Peripheral (USRP) Software Defined Radio (SDR) nodes. Through analytical and experimental studies, we compare the performance of LA-MAC with that of CSMA and TDMA under different traffic conditions. The results show the improvements achieved by LA-MAC in comparison with other alternatives.

In this paper, we propose an optimization framework for real-time voice transmission over wireless tandem channels prone to both bit errors and packet erasures. Utilizing a hybrid media dependent and media independent error correction scheme, our proposed framework is capable of protecting voice packets against both types of errors. For each group of frames associated with one speech spurt, the framework finds the optimal parity assignment of each voice frame according to its perceptual importance such that the quality of the received group of frames is maximized. Our performance evaluation results show that the proposed scheme outperforms a number of alternative schemes and has a low computational complexity.

Coping with collisions is one of the biggest challenges in the design of MAC algorithms for wireless networks. Recent advances in MIMO communications have provided the possibility of decoding colliding packets. In this paper, we introduce a new MIMO cross-layer MAC/PHY design that is capable of combating collisions through the use of a multiple packet detection technique. Analytical and simulation results show that the proposed MAC design can considerably improve the throughput of a WLAN operating over lossy links.

Many of the recently proposed high performance congestion control protocols rely on an estimation of the available link bandwidths. Specially, XCP and VCP need an explicit knowledge of the link bandwidth. However, wireless networks are characterized by bandwidth variations due to the openness of air links. Experiments have clearly shown that operating over variable bandwidth wireless links can lead to a significant performance degradation of congestion control protocols. Such degradation is typically measured in terms of oscillatory behavior. In this paper, we propose the use of an Extended Kalman Filter (EKF) to filter out the impact of bandwidth variations from the operation of wireless congestion control protocols. Our EKF-based Bandwidth Estimation (EBE) scheme can predict link capacity by monitoring the persistent queue size of a wireless link thereby eliminating the need for direct measuring of the real-time bandwidth. We implement EBE in NS-2 and integrate it with XCP and VCP protocols. Through extensive simulation studies, we demonstrate significant performance improvements of both protocols as the result of using EBE.

Recently, Variable-structure Congestion-control Protocol (VCP) has emerged as a great practical alternative of deployment for congestion control by requiring the use of only two ECN bits in the IP header. However, VCP suffers from a relatively low speed of convergence and exhibits biased fairness in moderate bandwidth high delay networks due to utilizing an insufficient amount of congestion feedback. Our previous work Double-Packet Congestion-control Protocol (DPCP) addressed this problem by increasing the amount of the feedback distributed over two ECN bits in the IP header of a pair of packets. However, DPCP faces deployment obstacles in encrypted wireless networks due to the fact that it relies on partial information in the TCP header and the TCP header information is lost when crossing encryption boundaries. Furthermore, wireless networks are characterized by both error- and congestion-caused loss. Our previous work has revealed that the efficiency of DPCP, and for that matter any congestion control protocol, over wireless networks may be reduced as the result of not being able to differentiate between two types of loss. In this paper, we propose an alternative congestion control protocol to which we refer as Distributed Congestion-control Protocol for Encrypted Wireless (DCP-EW) networks. DCP-EW is capable of efficiently operating in encrypted wireless networks while preserving all of the benefits of DPCP for wired networks. It does so by passively utilizing the IP Identification field of a packet header instead of the TCP header in conjunction with a heuristic algorithm to differentiate between different sources of loss. We implement DCP-EW in NS-2 and the Linux Kernel. We demonstrate the performance improvements of DCP-EW compared to DPCP and VCP through simulation and experimental studies.

We analytically model the distortion of a scalable video bitstream containing a Base Layer (BL) and one or more Enhancement Layers (ELs). Utilizing our distortion model, we propose a pair of low complexity Unequal Error Protection (UEP) methods for transmitting BL and EL bitstreams over a wireless channel. Our one dimensional Forward Error Correction (FEC) UEP methods protect each bitstream against both temporally correlated bit errors caused by fading and packet erasures caused by network buffering. Our methods use optimal symbol interleaving to combat tandem loss effects. We illustrate the performance advantage of our methods over a baseline Equal Error Protection (EEP) and a number of UEP methods for different available budgets and channel conditions.

In this paper, we present an optimization framework for transmitting high quality audio sequences over error-prone wireless links. Our framework introduces apparatus and technique to optimally protect a stored audio sequence transmitted over a wireless link while considering the packetization overhead of audio frames. Utilizing rate compatible punctured Reed-Solomon (RS) codes and dynamic programming, it identifies the optimal assignment of parity to audio frames according to their perceptual importance such that the segmented SNR of the received audio sequence is maximized. Our framework covers two cases. In the first case, a frame grouping technique is proposed to packetize audio frames and protect them against temporarily correlated bit errors introduced by a fading wireless channel. In this case, each packet is treated as a channel coding codeword. In the second case, a one-dimensional RS coder is applied vertically to a sequence of horizontally formed packets associated with an audio sequence in order to protect the sequence against both bit errors introduced by fading wireless channels and packet erasures introduced by network buffering. Our numerical results capture the performance advantage of our framework compared to existing techniques proposed in the literature of audio transmission. We also note that our framework can be generically applied to a variety of audio coders, making it attractive in terms of implementation.

Every congestion-control protocol operating in wireless networks is potentially faced with two major challenges of performance degradation. These sources are: 1) the coupling of fairness and efficiency; and 2) not properly differentiating between congestion-caused loss associated with network buffering and error-caused loss associated with fading effects. In this paper, we provide a Variable-structure Congestion-control Protocol (VCP)-based cross-layer framework of congestion control that can address both challenges noted. As a part of our framework, we introduce a loss differentiation heuristic algorithm that can be used with a variety of congestion-control protocols. Then, using analysis, simulation, implementation, and emulation, we profile the performance of a number of congestion-control alternatives in wireless networks. We describe the first implementation of VCP as a collection of loadable kernel modules along with fine-tuned implementations of XCP and TCP/AQM + ECN in Linux. We utilize NS2 as our simulation tool and a wired Linux testbed emulating wireless link effects as our experimental tool. We implement a finite-state Markov chain in both NS2 and our testbed in order to model error-caused loss over wireless links. We further use link-layer forward error correction (FEC) codes on a per-packet basis to compensate against such loss. Our profiling results demonstrate that VCP equipped with our loss differentiation heuristic and link-layer FEC represents a well-performing yet practical alternative of wireless congestion control. We also identify some of the shortcomings of VCP, including its oscillatory behavior in the presence of link estimation errors and poor fairness characteristic in multibottleneck networks.

We introduce an analytical expression for the expected distortion of a single layer encoded video bit-stream. Based on the expected distortion model, we propose a distortion optimal Unequal Error Protection (UEP) technique to transmit such bit-stream over a wireless tandem channel. The proposed method allocates the total transmission budget unequally to different frames of a video bit-stream in order to protect the bit-stream against both bit errors caused by fading and packet erasures caused by network buffering. We compare this technique with another UEP technique as well as a one-dimension equal length protection technique. The evaluation results for different choices of packet sizes, available budgets, and channel conditions show that the proposed method outperforms the other alternative schemes.

The performance of prevalent MAC protocols in MANETs relies on the level of contention in networks. While contention-based MAC protocols such as CSMA suffer from inefficiency under high contention, slot-based MAC protocols such as TDMA perform in the opposite way. In this paper, we propose a hybrid protocol to which we refer as Load-Adaptive MAC (LA-MAC) protocol for MANETs. By adaptively switching its running mode between CSMA and TDMA, LA-MAC achieves high channel utilization under both high and low contention. We report our implementation of LA-MAC on a MANET testbed formed by a collection of Multiple-Input Multiple-Output (MIMO) Universal Software Radio Peripheral (USRP) software defined radio nodes. We program the PHY layer of USRP nodes using GNU Radio and integrate LA-MAC with the PHY layer implementation of USRP. Through experimental studies, we demonstrate the performance improvements of LA-MAC relative to CSMA and TDMA.

Following the design philosophy of XCP, VCP is a router-assisted congestion protocol that intends to balance the efficiency and the fairness control in high Bandwidth-Delay Product networks. While both VCP and XCP achieve comparable performance, VCP represents a more practical alternative of deployment as it only requires the use of two ECN bits in the IP header. However, the use of two ECN bits only allows for establishing three levels of congestion notification signaling. Our previous work reveals that VCP suffers from relatively low speed of convergence and exhibits a biased fairness behavior in moderate bandwidth high delay networks due to utilizing an insufficient amount of congestion feedback. In this paper, we propose a distributed ECN-based congestion control protocol to which we refer as Double-Packet Congestion Control Protocol (DPCP). DPCP is capable of relaying a more precise congestion feedback compared to earlier proposed Variable-structure Congestion-control Protocol (VCP) yet preserving the utilization of the two ECN bits. By distributing (extracting) congestion related information into (from) a series of packets, DPCP is able to circumvent the limitations of VCP related to the use of three congestion levels encoded into two ECN bits. We implement DPCP in Linux and demonstrate its performance improvements compared to VCP through experimental studies.

In this paper, we propose a statistical optimization framework for transmitting audio sequences over wireless links. Our proposed framework protects audio frames against both temporally correlated random bit errors introduced by a fading channel and packet erasures caused by network buffering. Forming a two-dimensional grid of symbols, our framework forms horizontal packets that are compensated only vertically against both types of errors. The utilized one-dimensional error correction coding scheme of our framework assigns parity bits according to the perceptual importance of frames such that the Segmented SNR of a received audio sequence is maximized. In addition, the proposed framework suggests an effective way of reducing the packetization overhead of small audio frames.

We identify an analytical expression for the distortion of a scalable video bitstream. Relying on the distortion expression, we propose a low complexity distortion-optimal unequal error protection (UEP) method for the transmission of such video bitstream over wireless tandem channels. Utilizing a one-dimensional forward error correction (FEC) coding scheme, our proposed transmission method protects the bitstream against both bit errors caused by fading and packet erasures caused by network buffering. Our coding scheme also leverages symbol interleaving to better cope with the temporally correlated loss observed over the tandem channels of interest. We evaluate the performance of our proposed scheme by comparing its results against those of UEP product codes as well as those of optimized version of equal error protection (EEP). For a variety of choices of fixed packet sizes, available budgets, and channel conditions, we illustrate the performance advantage of our scheme over other schemes. Our experiments also show that our scheme works more efficiently for channels with a higher probability of bit errors than those with a lower probability of bit errors.

Achieving minimal loss while satisfying an acceptable delay profile remains to be an open problem under the RED queuing discipline. In this paper, we present a framework targeted at optimal fine tuning of the RED parameters in order to address such problem. For a given traffic pattern and utilizing a statistical analysis of finite-state Markov chains, we formulate an optimization problem aimed at addressing the loss and delay tradeoff of the RED queuing discipline. Our two-step iterative solution to the problem identifies the optimal settings of the RED parameters. We prove the convergence of our solution and investigate its low complexity characteristics. We apply our framework to a number of generic queuing and TCP scenarios in order to capture loss and delay performance of our algorithms versus buffer capacity and service rate. Based on our results, we argue that our model is capable of optimally addressing the loss-delay tradeoff of RED queues accommodating time-varying traffic profiles.

In this paper, we present an optimal UEP framework for transmitting packetized audio streams over MIMO wireless links. Our proposed framework aims at maximizing the expected end-to-end Segmented SNR of a received audio sequence. It reduces the packetization overhead of small audio frames while protecting audio streams against temporarily correlated bit errors introduced by wireless transmission medium. To reduce the packetization overhead, our framework suggests a frame grouping technique distributing the transmission overhead of one packet among multiple audio frames. To mitigate the effects of random bit errors, our framework utilizes a UEP RS channel coding scheme to assign parity bits according to the combined perceptual importance of frames embedded in individual packets.

In this paper, we propose an analytical model to capture the dynamics of the RED algorithm. We first develop a system of recursive equations that describes the packet dropping behavior of the RED algorithm. Using a notion from the theory of random walks, we then derive an exact-closed form expression that characterizes the loss characteristics of a RED queue. We validate the derived formula by a numerical comparison with the recursive equations.

We describe a cross-layer study that attempts at profiling the performance of end-to-end congestion control protocols in high BDP wireless networks. Packets transmitted over such networks are assumed to face temporally correlated random bit errors caused by fading and/or blocking. We utilize a finite-state Markov chain to model bit error characteristics and apply per packet link layer FEC codes in order to compensate for such errors. Utilizing our model along with loss expressions, we profile the end-to-end performance of XCP, VCP, and TCP/AQM+ECN congestion control protocols. Based on our profiling results, we observe that (1) the performance of any congestion control protocol highly degrades without properly protecting its data and signaling information against random bit errors, (2) utilizing multiple antenna nodes improves the transient characteristics of the congestion control protocol in terms of utilization and packet error rates, and (3) XCP and VCP represent the best alternatives of congestion control for high bandwidth moderate delay and moderate bandwidth large delay environments, respectively.

We study the effects of physical layer parameters on the connectivity of fading ad-hoc networks. Relying on a symbol error rate connectivity metric for such networks, we assume a pair of nodes are connected if their bi-directional measure of connectivity satisfies a given threshold. We investigate the effects of three parameters on the connectivity phenomenon. First and assuming the nodes are distributed over a fixed finite area, we study the effects of the changes in nodes' density. Next, we measure the connectivity effects of the interference coefficients, i.e., the portion of power an interfering node contributes to other links. Finally, we experiment with the threshold of link quality for connectedness. For each parameter, we also provide an intuitive explanation of the phenomena observed in our experiments. Our simulation results show that (1) depending on the value of interference coefficient, an increase in node density may increase or decrease, and (2) increasing the interference coefficients and thresholds of link quality will decrease the connectivity of fading ad-hoc networks.

We study constrained resource allocation problems for MIMO wireless ad-hoc networks under LOS fading. By considering the tradeoff between the aggregate consumed power and throughput of such networks, we investigate the performance characteristics of a number of MIMO coding techniques, namely MRC, STBCs, and orthogonal STTCs. Our study shows that utilizing space-time coding techniques can decrease the power consumption and/or increase the achievable throughput of ad-hoc networks under loss constraints

We study the problem of real-time error control in layered and replicated media systems. We formulate an optimization problem aimed at minimizing a cost metric defined over the wasted bandwidth of redundancy in such systems. We also provide an analytical solution to the problem in the context of layered media multicast control (LMMC) protocol. In doing so, we present closed-form expressions describing the temporally correlated loss pattern of communication networks. Utilizing our closed-form expressions, we rely on an a priori estimate of loss along with a hybrid proactive FEC-ARQ scheme to statistically guarantee the QoS for the receivers of a media system. We show the effectiveness of our protocol by means of simulating realistic error control scenarios

We study the problem of connectivity in MIMO fading ad-hoc networks. Based on a probabilistic analysis of achievable capacity on individual links of a random topology, we introduce a novel connectivity metric for wireless ad-hoc networks. We assume a pair of nodes are connected if their bi-directional capacity is more than a given threshold. Our metric is more sophisticated compared to previously proposed metrics of connectivity as it captures the effects of time-varying fading channel, power, and multiple antennas. Our results show that employing mobile nodes with multiple antennas enhances the connectivity of fading wireless ad-hoc networks

We propose a novel distortion minimization technique for the transmission of a packetized progressive bitstream. We consider tandem channels introducing bit errors and packet erasures. We formalize the distortion minimization problem as a constrained optimization problem and propose an algorithm that optimally allocates the available budget between the bit error and packet loss protection components. We show that our proposed optimization technique is robust and has a linear complexity in the transmission rate. Numerical results show the effectiveness of the proposed algorithm.

We propose a novel distortion minimization technique for the transmission of a packetized progressive bitstream. The optimality of our proposed algorithm is analytically proved for a class of sources satisfying a stated condition. It is shown that Gauss-Markov sources belong to the latter class for which the algorithm is optimal. We show that our proposed optimization technique is robust and has a linear complexity in the transmission rate. Simulation results show the effectiveness of our proposed algorithm.

Buffer management in queuing systems plays an important role in addressing the tradeoff between efficiency measured in terms of overall packet loss and fairness measured in terms of individual source packet loss. Complete partitioning (CP) of a buffer with the best fairness characteristic and complete sharing (CS) of a buffer with the best efficiency characteristic are at the opposite ends of the spectrum of buffer management techniques. Dynamic partitioning buffer management techniques aim at addressing the tradeoff between efficiency and fairness. Ease of implementation is the key issue when determining the practicality of a dynamic buffer management technique. In this paper, two novel dynamic buffer management techniques for queuing systems accommodating self-similar traffic patterns are introduced. The techniques take advantage of the adaptive learning power of perceptron neural networks when applied to arriving traffic patterns of queuing systems. Relying on the water-filling approach, our proposed techniques are capable of coping with the tradeoff between packet loss and fairness issues. Computer simulations reveal that both of the proposed techniques enjoy great efficiency and fairness characteristics as well as ease of implementation.

The objective of layering techniques of distributing multimedia traffic over multicast IP networks is to effectively cope with the challenges in continuous media applications. The challenges include heterogeneity, fairness, real-time constraints, and quality of service. We study the problem of rate allocation and receiver partitioning in layered and replicated media systems. We formulate an optimization problem aimed at maximizing a close approximation of the so-called max-min fairness metric subject to loss and bandwidth constraints. Our optimal layered media multicast control (LMMC) solution to the problem analytically determines the layer rates and the corresponding partitioning of the receivers. Our simulation results show the effectiveness of our proposed solution in realistic scenarios.

We present a statistical optimization framework for solving the end-to-end problem of progressive transmission of images over noisy channels. We consider the impacts of transmission bit errors as well as packet erasures. To cope with the impact of random bit errors, we formulate an optimization problem aimed at minimizing the end-to-end expected distortion of a reconstructed image subject to rate and efficiency constraints. In order to eliminate the impact of packet erasures, we propose utilizing an algorithm that is capable of statistically guaranteeing the delivery of a packet set associated with the progressive bitstream of an image source. Using receiver feedback, our framework is capable of effectively coping with the channel loss effects characterized by the Gilbert-Elliott model.

In this paper, we present an analytical solution to the problem of rate allocation and receiver partitioning in layered media systems. The framework of our proposed protocol layered media multicast control (LMMC) determines the layer rates and the corresponding partitioning of the receivers maximizing a mathematically well-behaved approximation of the so-called max-min fairness metric.

Addressing the tradeoff between the QoS and consumed power is a critical issue for wireless ad-hoc networks. The loss observed in such networks is often temporally correlated. This paper examines an optimal scheme to maximize the aggregate data rate of wireless ad-hoc networks under the power and loss constraints. In order to properly model temporally correlated loss observed in a fading wireless channel, we propose the use of finite-state Markov chains. Details of fading statistics of SIR, an important indicator of transmission quality, are presented. We also analyze the impacts of enforcing power, block-loss probabilities, and data rates constraints.

We present analytical and numerical solutions to the problem of power control in wireless media systems with multiple antennas. We formulate a set of optimization problems aimed at minimizing total power consumption of wireless media systems subject to a given level of QoS and an available bit rate. Our formulation takes into consideration the power consumption related to source coding, channel coding, and transmission of multiple-transmit antennas. In our study, we consider Gauss-Markov and video source models, Rayleigh fading channels along with the Bernoulli/Gilbert-Elliott loss models, and space-time block codes.

In this research article, we present an analytical solution to the problem of power control in wireless media systems with multiple transmit antennas. We formulate an optimization problem aimed at minimizing total power consumption of wireless media systems subject to a given level of quality of service (QoS) and an available bit rate. Our formulation takes into consideration the power consumption related to source coding, channel coding, and transmission of multiple transmit antennas relying on the H.263 source coding standard, Rayleigh fading channels along with the Bernoulli loss model, and space-time block codes respectively.

We present an analytical study for the Gilbert loss model describing temporally correlated loss observed in the Internet and other communication systems. We obtain closed-form solutions describing the transient and steady-state behavior of the model. Additionally, starting from recursive equations of the Gilbert loss model, we derive closed-form solutions for arrival and loss patterns of the systems governed by the model. We show that utilizing our model yields a lower complexity compared to existing recursive models, attracting special attention for use in many different wired and wireless networking applications relying on such a model.

In this paper, we present an optimal solution to the problem of error control in layered and replicated media systems satisfying real-time delay constraints. In doing so, we rely on an a priori estimate of loss along with a hybrid proactive FEC-ARQ scheme to statistically guarantee the quality of service for receivers. Our optimal layered media multicast control (LMMC) solution to a formulation of the error control problem analytically determines the redundancy assignment of individual groups associated with a layered media system minimizing a cost metric defined over wasted bandwidth of redundancy.

Reducing packet loss and increasing overall efficiency in multiple source queuing systems is one of the most important issues in the design of traffic control algorithms. On the other hand, the other important issue in such systems is to provide every individual source with the ability to take advantage of a fair portion of the shared available resources such as buffer space or server bandwidth. In this paper a novel technique for reducing packet loss in a class of queuing systems with self-similar traffic patterns is introduced. The technique takes advantage of the modeling power of neural networks to offer a dynamic buffer management scheme capable of efficiently addressing the trade off between packet loss and fairness issues.