This paper studies the learning performance of the Proximal Policy Optimization (PPO) algorithm in the challenging use case of uncoordinated and distributed multi-agent (UDMA) resource allocation in a cognitive radio network (CRN) via an underlay dynamic spectrum access (DSA) paradigm. The challenge is to establish whether PPO will converge faster to the best performance policies than UDMA-DQL in the non-stationary environment. The simulation results show that the UDMA-PPO achieves faster learning performance than UDMA table-based Q-learning and UDMA deep Q-learning (DQL) and is robust to the non-stationary environment. The UDMA-PPO achieves better performance with about 70 % less training steps compared to the UDMA-Table and achieves similar performance with 25% less training steps than the UDMA-DQL algorithm.

The next decade is poised for a transformative shift in wireless communication technologies, driven by the increasing demand for data-intensive applications. Innovations in signal processing, network architecture estimation and design, and spectrum utilization will be critical in realizing the potential of 5G and beyond. These advancements will enable the seamless integration of emerging technologies and empower the digital transformation of industries and society. In this paper, we introduce a Variational Autoencoder (VAE) based model for indoor radio propagation modeling within an automated Industry4.0 warehouse or factory floor in the 5G wireless bands. We detail the creation of training data tensors, the architecture of our proposed VAE model, and its training using tensors that capture the impact of various interacting objects within a 5G-enabled smart warehouse infrastructure. The model is trained on multiple warehouse configurations to predict the signal-to-interference-plus-noise ratio (SINR) for both the validation dataset and unknown warehouse configurations. We present reconstruction error heatmaps to demonstrate the accuracy of our model and analyze its performance in different complex warehouse environments.

The lack of quality datasets is a critical problem that limits machine learning experimentation in the areas of intelligent networks and security. Datasets are often a poor fit, insufficient for experiment needs, out of date or simply inaccessible. To address these issues we present the RIT dataset collections. These two collections consist of balanced and unbalanced capture files, topology diagrams and scenario descriptions. The network capture files in the collection are available in text and pcapng formats. The base network collection also contains image files created from the packet capture data samples. These formats offer researchers an unparalleled opportunity to benchmark a wider variety of machine learning models. The balanced training and validation datasets contain 5,000 and 500 samples for each of fourteen classes. Classes include TCP and UDP variations, layer 3 protocols such as the Address Resolution Protocol and layer 2 management protocols such as spanning tree. The base collection includes five other curated but unbalanced test sets. Expanding on the original fourteen classes, typical network activities are captured in the second set of uncurated files. The security collection includes capture files, topology diagrams and the associated scenario descriptions. The current collection consists of Man in the Middle (MITM) attacks, TCP port scans and Active Directory (AD) enumeration attacks. Additional datasets and their topology diagrams continue to be added to the collections. The repository also provides some multi-layer perceptron and convolutional neural network model classification accuracy values for comparison. The dataset collections are publicly available via RIT Scholar-works and the following DOIs: www.doi.org/10.57673/gccis-yg55 and www.doi.org/10.57673/gccis-qj60

By virtue of being an efficient way to distribute network resources to physical groups of users and to allow the network to provide performance guarantees, network slicing is one of the main features that has been included in 5G wireless networks. Concurrently, 5G networks will improve the spectral efficiency by transmitting over multiple RF bands (carrier aggregation), some potentially shared with other networks. This work presents a novel approach to implement network slicing when a network is sharing some of its spectrum bands with another network, making it first of its kind in addressing network slicing in a spectrum sharing environment. In the proposed technique, graph coloring is used to represent the interference between two networks and to assign spectrum resources to each access. In addition, two mechanisms are introduced to manage interference: "gray zones" and "blurred edges", the latter of which specifically address inter-network interference. Results show that the proposed technique is effectively able to perform resource allocation for network slicing in a shared spectrum environment by meeting throughput requirements for all slices and the isolation of services that is expected from network slicing.

A fundamental goal for the sustainable operation of wireless networks is that they are able to continue to provide service in the presence of events that disrupt their electrical power supply. This paper introduces the concept of virtual energy transfer, a novel technique that increases the physical resiliency of state-of-the-art wireless networks by leveraging dual connectivity transmissions. With virtual energy transfer, a base station with higher resiliency and more energy stored locally for electrical power backup participates in a dual connectivity transmission with another base station that sees its resiliency increased by consuming less energy, which translates in an equivalent increase in the energy stored locally. Simulation results show that the proposed technique is effective in increasing the physical resiliency of the small cell site receiving the virtual transfer while keeping the resiliency of the larger cell site originating the virtual transfer at levels sufficiently large. It is also seen that the proposed technique can be used to provide useful reduction in the sizing requirements of local energy buffers and significantly extends the time a base station can operate powered from locally stored energy.

With the rapid growth of vehicles, the vehicular networks meet main challenges such as dynamic, heterogeneous, and large scaled. In addition, the cellular-based vehicular networks must satisfy further strict requirements, including ultralow latency, high reliability, high spectrum efficiency, and massive connections of the next-generation (6G) network. Recently, by exploiting vehicle clustering utilized for reducing the complexity of vehicle-to-everything (V2X) systems, it could ultimately improve road traffic efficiency. In some specific scenarios related to Internet of Things, a group of vehicles can be served effectively in terms of spectrum efficiency when two key techniques are enabled, i.e., nonorthogonal multiple access and cognitive radio (CR) schemes are joint deployed. These techniques certainly benefit to 6G V2X services to reduce specific challenges, such as traffic congestion and massive connections. Different from existing works, we propose wireless power transfer applied to the roadside unit to improve the situation that energy shortening in small devices deployed in V2X communications. In particular, we derive expressions of throughput to exhibit performance of the two grouped vehicles. To further indicate advantages of spectrum efficiency, we compare two schemes of V2X systems with and without CR schemes. The numerical results demonstrate that the non-CR NOMA-V2X scheme outperforms the CR-based NOMA-V2X scheme with fixed power allocation, but the non-CR NOMA-V2X scheme costs higher spectrum resource compared with the counterpart. Besides, by comparing with orthogonal multiple access (OMA)-assisted V2X, NOMA-V2X schemes demonstrate superiority in terms of throughput performance whilst achieving the benefits of both NOMA and CR schemes.

Utilizing millimeter wave (mmWave) wireless communication in wireless datacenter networks, the power consumption of the networking equipment can be reduced drastically. However, security of a datacenter is one of the highest design priorities. Many studies on the security of wired datacenters including identifying the possible threats and solutions have been explored in the literature. On the contrary, being an emerging technology, no study has been conducted on the security for the wireless datacenters. Being a wireless system, it has the potential to inherit many of the threats of a typical wireless network. So, in order to successfully realize wireless datacenter architectures, it is essential to do an extensive investigation of the system from a security perspective. In this paper, we study both existing as well as novel threats and their impact on the wireless datacenter network. In addition to these conventional threats, we demonstrate the impact of a novel attack on the wireless datacenter which can be launched by leveraging its control plane.

One of the primary goals in machine learning with neural networks is to reduce training time while simultaneously maintaining or improving accuracy. To this end a variety of optimization techniques have been developed and implemented. For the researcher focusing on particular datasets it is not always clear what works best for a given task. Dataset construction can also have a dramatic effect on results. This paper studies optimization algorithms with completely balanced packet traffic datasets and provides performance criteria for training time and accuracy. The importance in using completely balanced datasets is discussed and demonstrated. We show that though several algorithms can achieve near 99% accuracy while keeping training times to less than one minute, there is wide variation and unpredictability in some. The investigation was completed using 65K training samples, a 6. 5K validation set and four test datasets. Finally we examine varying neural network structures that might improve an algorithms performance and find that wider or deeper networks are often more of a problem than help.

Cognitive radio networks (CRNs) implementing spectrum sharing between primary and secondary users are able to provide a needed solution for the increasing spectrum scarcity problem. This paper presents a cross layer resource allocation scheme for underlay dynamic spectrum access (DSA) in cognitive radio networks with a goal to improve end-to-end Quality of Experience (QoE) for video traffic, as measured through the Mean Opinion Score (MOS). The presented solution implements a deep Q-network (DQN) that allows a CR to perform resource allocation by observing the environmental variables over physical and network layers and takes actions to update its own parameters across these layers in order to maximize the MOS for its interactive video stream, all while maintaining interference to the primary users below a threshold limit. Simulation results show that perceived quality for the transmitted video using the proposed cross-layer scheme outperforms a benchmark comparable DQN scheme that adapts only the physical layer, often yielding an improvement of one grade scale in the MOS. Moreover, the proposed cross-layer DQN scheme achieves a balanced load on a network with routers with unequal service rates.

This paper studies the problem of spectrum-aware routing in a multi-hop, multi-channel cognitive radio network when malicious nodes in the secondary network attempt to block the path with mixed attacks. Based on the location and time-variant path delay information, we model the path discovery process as a non-cooperative stochastic game. By exploiting the structure of the underlying Markov Decision Process, we decompose the stochastic routing game into a series of stage games. For each stage game, we propose a distributed strategy learning mechanism based on stochastic fictitious play to learn the equilibrium strategies of joint relay-channel selection in the condition of both limited information exchange and potential routing-toward-primary attacks. We also introduce a trustworthiness evaluation mechanism based on a multi-arm bandit process for normal users to avoid relaying to the sink-hole attackers. Simulation results show that without the need of information flooding, the proposed algorithm is efficient in bypassing the malicious nodes with mixed attacks.

Datacenters have become the digital backbone of the modern society and consume enormous amounts of power. Significant portion of the power consumption is due to the power hungry switching fabric necessary for communication in the datacenter. Additionally, the complex cabling in traditional datacenters pose design and maintenance challenges and increase the energy cost of the cooling infrastructure by obstructing the flow of chilled air. In this work we address these problems of traditional datacenters by designing a server-to-server wireless datacenter network (DCN). We propose design methodologies for the use of 60GHz unlicensed millimeter-wave bands to establish direct communication links between servers in a DCN without the need for a conventional fabric. This will reduce the power consumption of the DCN significantly. We first demonstrate that such a power-efficient wireless DCN can sustain the traffic requirements encountered in small to mid-size real datacenters and provide data rates that are comparable to traditional DCNs. Having established the feasibility of a server-to-server wireless DCN in terms of performance, we estimate that its power consumption is lower by four to six times in comparison to a conventional DCN fabric.

In this paper, we study the power allocation problem for the downlink transmission in a set of closed-access femtocells which underlay a number of macrocells. We introduce a mutli-step pricing mechanism for the macrocells to control the cross- tier interference by femtocell transmissions without explicit coordination. We model the cross- tier joint power allocation process in the heterogeneous network as a non-cooperative, average-reward Markov game. By investigating the structure of the instantaneous payoff functions in the game, we propose a self-organized strategy learning scheme based on learning automata for both the macrocell base stations and the femtocell access points to adapt their transmit power simultaneously. We prove that the proposed learning scheme is able to find a pure-strategy Nash equilibrium of the game without the need for the femtocell access points to share any local information. Simulation results show the efficiency of the proposed learning scheme.

Recent years have seen an increased concern for the power consumption in cellular networks and the consequent environmental impact. This paper studies the role that source (especially video) coding efficiency plays in reducing the power consumption of cellular networks, making its operation more environmentally sustainable. Specifically, this paper presents a formulation that describes the power savings at base stations when multimedia traffic relies on more efficient source codecs. In addition, this paper examines the impact that the recent introduction of the highly efficient H.265 video coding standard could have in green cellular networks. Results based on realistic settings show power consumption reduction by as much as 27% when video traffic is based on H.265 coding instead of H.264. When aiming at powering the base station from renewable energy, it is shown that the probability of having insufficient renewable energy is reduced by half when video traffic is based on H.265. Also, it is shown how increased video coding efficiency results in a significant reduction in the required physical footprint of renewable electric power generators and a notable increase in the lifetime of the battery banks that are needed to operate powered from renewable energy.

This paper addresses the problem of dynamic, real-time video transmission control over a time-varying wireless channel. The problem of adaptive source coding control is studied on the basis of scalable video coding schemes. A video-layer-based hybrid automatic repeat request scheme is adopted to achieve adaptive error protection allocation. The problem of joint source-channel resource allocation over a time-varying wireless channel is posed as a constrained Markov Decision Process (MDP). The goal of the proposed video streaming MDP is to minimize the average end-to-end frame distortion with the constraint on the average transmission time for each layer. In order to address the issue of unknown channel dynamics and inaccurate distortion model, the R-learning-based on-line algorithm is adopted for learning the transmission police. To handle the constrained MDP with the standard R-learning algorithm, the constrained MDP is converted into an unconstrained MDP through the Lagrangian approach. The efficiency and convergence of the proposed learning algorithm are demonstrated with the simulation results.

This paper studies a cross-layer technique to increase the powering of an LTE macro base station from renewable energy. The cross-layer technique integrates the management of the transmit antennas and LTE frames with, at the application layer, video compression factor and data traffic delay. Importantly, the management of these cellular network components is integrated with the base station energy system by adapting the transmission of the cellular network based on the projected renewable energy availability. The overall system presents a tradeoff between increased use of renewable energy and an increase in video distortion and data delay up to predefined limits. Simulation results show that the studied technique effectively increases the percentage of time that an LTE base station is able to operate powered only from renewable energy (up to 98.5%) while at the same time increasing within small, acceptable levels, video distortion and data delay a third of the time.

The work in this paper studies the performance of Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) medium access control (MAC) mechanism in IEEE 802.11 DCF. From studying the propagation delay and clock synchronization differences between terminals, it is concluded that the slight timing differences, effectively a relative jitter, contributes to reducing the probability of collisions after a MAC backoff. This lesson is leveraged in a presented new CSMA/CA MAC technique that deliberately introduces a random short delay, akin to jitter, in the backoff slots time structure. The new medium access technique is evaluated through both an analytical model and simulations that consider the realistic timing constraints set in the IEEE 802.11 standard. Simulation results show improvements in normalized saturated throughput with the new technique from at least 14% for 10 nodes up to 26% for 50 nodes.

A green-energy-powered, self-sustainable cellular network is studied in this paper. To address the problem of the energy variability in the green sources, a joint energy-traffic management mechanism is proposed based on game theory. The interaction between the cellular network and a microgrid power controller is modeled as a two-level Stackelberg game. On the network level, an iterative combinatorial auction mechanism is proposed to solve the joint power-subcarrier allocation problem. On the microgrid level, an adaptive pricing mechanism is adopted for the power controller to balance between the transmission demand and the energy supply. Simulation results show that the proposed resource allocation mechanism achieves a significant improvement in the network sustainability and throughput when compared with the conventional resource allocation method.

This paper presents a technique to reduce the carbon footprint of cellular network through the use of renewable energy as a power source. Novel to other approaches in the literature, the presented technique adapts the traffic conditions and Quality of Experience (QoE) goals. Through effectively integrating energy and traffic management, the presented technique shapes the traffic serviced by the base station based on the predicted renewable energy surplus or deficit, and by controllably reducing the real-time video quality and increasing the data traffic delay. Simulation results show an increase of fifty percent in the proportion of time that the base station is powered from renewable sources with a very small, controlled and bounded impact on real time traffic quality and data delay.

This paper investigates the energy-efficient power allocation for a two-tier, underlaid femtocell network. The behaviors of the Macrocell Base Station (MBS) and the Femtocell Users (FUs) are modeled hierarchically as a Stackelberg game. The MBS guarantees its own QoS requirement by charging the FUs individually according to the cross-tier interference, and the FUs responds by controlling the local transmit power non-cooperatively. Due to the limit of information exchange in intra-and inter-tiers, a self-learning based strategy-updating mechanism is proposed for each user to learn the equilibrium strategies. In the same Stackelberg-game framework, two different scenarios based on the continuous and discrete power profiles for the FUs are studied, respectively. The self-learning schemes in the two scenarios are designed based on the local best response. By studying the properties of the proposed game in the two situations, the convergence property of the learning schemes is provided. The simulation results are provided to support the theoretical finding in different situations of the proposed game, and the efficiency of the learning schemes is validated.

This paper proposes a distributed routing mechanism for the multi-hop Cognitive Radio Networks (CRNs) over multiple primary channels. The Secondary Users (SUs) attempts to utilize the channels and minimize their delay along the route while avoiding causing interference to the Primary Users (PUs). In order to address the problem of time-varying channel condition due to the PU dynamics, the route-selection process is modeled as a global Markov Decision Process (MDP). We show that such a global routing MDP can be decomposed into the layered MDPs, in which the interactions between neighbor SUs with their local next-hop selection are modeled as the local stochastic games. By applying reinforcement learning with utility based fictitious play, the best response of each SU can be learned from the local game with the only need for the information exchange from next-hop SUs. The proposed algorithm is evaluated through simulations and is shown to be effective in reducing the delays for multiple flows in the CRN.

This paper proposes a robust, spectrum-aware routing mechanism for the multi-hop, multi-channel Cognitive Radio Networks (CRNs) that are exposed to the Routing-toward-Primary-User Attack (RPUA). With RPUA, malicious Secondary Users (SUs) attempt to block the data transmission of the normal SUs by routing packets towards the SUs around the Primary Users (PUs). The proposed routing mechanism models the interaction between the non-malicious SUs and their one-hop neighbors as a stochastic game. With routing information back-propagation from the next-hop SUs, the local relay-channel-selection games along the routing path form a global, layered Markov Decision Process (MDP). To address the problem of the mixed attack with both RPUA and Sink-Hole-Attack (SHA), the trustworthiness of the neighbor nodes is evaluated as a single-buyer-multiple-seller price competition. For each SU, the best policy of relay-channel selection is learned in a reinforcement learning framework with fictitious play. Simulation results show that the proposed routing algorithm can avoid malicious relays and minimize the routing delay in the CRN under attacks.

Multihop communication links in conventional Networks-on-Chips (NoCs) results in lower rates of data transfer and higher energy dissipation. Long-range millimeter-wave wireless interconnects were envisioned to alleviate this problem. However, the available bandwidth of the wireless channels is limited and hence an efficient media access control (MAC) scheme is required to enhance the utilization of the available bandwidth. In this article we show that with multiple simultaneous access of the shared wireless medium using a Code Division Multiple Access (CDMA) scheme the peak performance can be improved significantly while lowering energy dissipation in data transfer compared to the conventional wireline counterparts as well as state-of-the-art Wireless NoCs using similar technologies. We present a thorough analysis of the reliability in data transfer using the CDMA based wireless links and show that a reliability-aware architecture design with CDMA based wireless links can lower the energy dissipation in NoC fabrics without compromising the achievable robustness.

In recent years, cross-layer Resource Management (RM) has been widely considered as an efficient approach for improving the network performance. However, due to the factors such as limited knowledge about the wireless environment and spontaneous characteristics of device behaviors, designing an efficient distributed RM scheme using the cross-layer paradigm becomes extremely difficult. In this paper, a distributed, cross-layer RM scheme for multi-users transmitting scalable video in an ad-hoc CDMA network is presented. For the cross-layer RM design, an end-to-end performance criterion at the APP layer is applied and the resource allocations in the PHY, LINK and APP layers are unified into a single decision process. Due to the dynamic property of the wireless channels and the uncoordinated user interactions, the distributed RM decision is modeled in the framework of stochastic game. In the game, each device gradually learns its policy using a distributed, Correlated Equilibrium (CE) based Q-Learning algorithm. In order to calculate the CE in a distributed way, the local devices apply the regret-matching based mechanism for policy and state-action value updating. Simulation experiments show that with the proposed resource management scheme, the system performance can be improved by about 15% compared to the layered RM scheme and 10% compared to the RM scheme purely based on the local-level learning.

Before achieving convergence, iterative resource allocation algorithms may result in degraded link quality that presents a challenge for the transmission of delay constrained multimedia traffic because of the impossibility for retransmission of frames received with errors. In this paper, a novel approach to solve this problem is presented by proposing the use of a source and channel coding scheme matched to the performance of the algorithm during iterations. The solution uses a JSCC scheme based on incremental redundancy and single feedback for transmission under strict delay constraints. The presented results, based on three widely representative iterative algorithms, show that the novel approach notably reduces the probability of transmissions with excessive distortion. The results show an increase of 12 % in relative values for the probability of links achieving target end-to-end distortion values, reduce the negative effects of degraded channels when performing iterations and also effectively absorb the effect of channel changes over time. These characteristics are specially useful for cognitive radio learning algorithms to mitigate the distortion increase during the exploratory phase.

This paper introduces an architecture for powering green mobile networks with a majority of renewable sources. The architecture makes use of wind turbines and photovoltaic panels as sources of electric power for cellular base stations. The electric power generators are located within the cellular network in a microgrid configuration. The microgrid configuration allows for a more efficient management of electric resources and a more resilient cellular system architecture. In addition, the microgid configuration allows for a management of the cellular network resources more tightly coupled with the electric power grid status and viceversa. The presented results will show that it is possible to power a cellular network from renewable source for us much as 90 % of the time. This work also discussed traffic shaping and management techniques so as to power off one cell to increase the use of renewable energy sources even when the traffic is not at a low level. The technique is effective in maintaining within reasonable values the reduction of voice traffic quality and the increasing in data queuing delay.

The mobile user population connected to the Internet continues to grow in number and hence provisioning seamless Internet service to such user is a topic of major interest. With new mobility architectures being investigated, it is important to have consistent comparative platforms and metrics. In this article, we introduce a novel and user-centric handoff cost framework to analyze handoff performance of different mobility schemes. The proposed framework helps examine the impacts of registration costs, signaling overhead, and data loss for Internet connected mobile users employing a unified cost metric. We first applied the framework to our future Internet mobility architecture, called Virtual Mobility Domains (VMDs). This architecture is user centric as it allows mobile users to avail services from overlapping mobility domains based on their mobility profiles. Next, the framework is applied to IPv6-based mobility protocols such as Hierarchical Mobile IPv6 and Proxy Mobile IPv6 to show the framework's flexibility and adaptability. Using the framework, we compare the handoff performance of IPv6-based mobility protocols to the VMD based mobility scheme. The results indicate that the handoff performance achieved with VMD is three and nine times superior to Proxy Mobile IPv6 and Hierarchical Mobile IPv6 respectively.

The ability to detect a particular speech codec from only the decoded audio has several useful forensic and system performance improvement applications. This paper presents a novel scheme for non-intrusive identification of speech codecs. The identification approach is based upon comparing a profile of a set of noise spectra and a time-domain histogram from the decoded speech to those from the candidate codecs. The presented results show a very high accuracy in identifying speech contemporary codecs from a diverse set of types and encoding rates. The presented codec identification scheme has a very low misidentification rate, including in the high coding rate regime where it improves on previous works by achieving perfect identification. This performance is achieved while reducing the duration of the analysis window of speech from 2 minutes to only 4 seconds.

Multi-hop data transfer in conventional Networks-on-Chips (NoCs) results in lower rates of data transfer and higher energy dissipation. Long-range millimeter-wave wireless interconnects were envisioned to alleviate this problem. However, as the bandwidth of the wireless channels is limited an efficient media access control (MAC) scheme is required to enhance the utilization of the available bandwidth. In this paper we show that with multiple simultaneous access of the shared wireless medium using a traffic-adaptive Code Division Multiple Access (CDMA) scheme the peak performance can be improved significantly while lowering energy dissipation in data transfer compared to the conventional wireline counterparts.

Guitar audio transcription is the process of generating a human-interpretable musical score from guitar audio. The musical score is presented as guitar tablature, which indicates what notes are played and where they are played on the guitar fretboard. Automatic transcription remains a challenge with polyphonic sounds as those generated by a guitar. The guitar adds more ambiguity to the transcription problem because the same note can be played in many ways. On the other hand, the guitar offers the potential to constrain the polyphonic pitch detection problem because it has few strings and the fingering is usually performed by a single hand. In this paper, a real-time guitar transcription scheme is presented. Accuracy is improved by considering physical limitations of the guitar and the human player.

While the research into MIMO communications algorithms have reached levels of development that show important wire less systems performance improvements, the development of DSP systems to implement them has limited implementations to the simplest and least performing algorithms. This paper addresses this technological gap by studying how to design DSP systems to better handle the increased complexity arising from the operations typical of MIMO algorithms. Two approaches are considered: adding new instructions to the DSP instruction set and adding a hardware accelerator to the DSP system. Of the two approaches, the second was concluded to be best, resulting in notable processing speedups and more efficient use of the computational resources.

Given its pervasive use, and being a clear example of a computing system integrating hardware and software, Digital Signal Processing (DSP) is an important discipline in Computer Engineering undergraduate curricula. This paper presents a DSP course that, in addition to traditional lectures and exercises, uses Matlab to provide a limited level of laboratory-type practice. Also, the use of demonstrations during lectures is presented. The presentations help the students relate the theoretical concepts presented in class with the technical area of expertise they are most comfortable with, that of hardware, software and their integration. The demonstrations are implemented using a portable laboratory with a DSP board and a small oscilloscope. Presented results show how the use of demonstrations has increased the overall rating for the course and how stimulating it is found.

A Cognitive Radio (CR) network has to adapt operations of all secondary users to meet performance goals while avoiding interfering the primary network (PN) beyond a set limit. For this, this paper considers a distributed cross-layer resource allocation CR algorithm. While the cross-layer approach notably improves performance in terms of average end-to-end distortion and network's congestion rate, it increases the number of iterations needed to find the resource allocation solution. In this paper, the extra complexity in the cross-layer approach is addressed through a novel cooperative cross-layer learning algorithm where peer nodes cooperate first distributing the learning tasks, followed by sharing of the complementary learned information. The algorithm does not rely on the availability of expert nodes that have already performed the learning process. Simulation results show that the cooperative learning technique reduces complexity by approximately 45% with a small and very acceptable sacrifice in performance.

The need for a reduction in healthcare cost has escalated over the past decade. Therefore, preventive medicine through remote health monitoring and Body Area Networks has gained more attention. This paper presents a novel Medium Access Control (MAC) protocol called Pulsed-MAC or simply PMAC to efficiently manage wireless communications in Body Area Networks. PMAC drastically extends the network life time by augmenting sensor nodes with charge pumping circuitry which harvest energy from a pulsed signal used to orchestrate communications. By measuring the average radio power consumption in a sensor node over a 24 hour simulation period, results show that PMAC outperforms conventional SMAC by up to three times and will easily allow for a Body Area Network to last beyond 200 days.

A challenge when enabling cooperation for conversational multimedia is how to obtain enough resources from the network. One approach is to use the source dynamics and allocate freed up resources from sources in low activity levels. This introduces a tradeoff between cooperation effectiveness and the networks ability to admit more users. This paper presents a scheme that incorporates the use of embedded source codecs, allowing for a tradeoff between source compression and cooperation effectiveness, without affecting the ability to admit more users. This increases the number of users that can be admitted to the network for a target received quality. A scheme is presented to decide when to trade off compression ratio for cooperation.

This paper studies TCP performance when running over a wireless network that implements cooperative communications. Two well-known cooperative communications schemes were considered: Amplify-and-Forward and Decode-and-Forward. Also, two cross-layer cooperative communications schemes that leverage on the link layer retransmission scheme were considered. These schemes transmit the message from the cooperating node only when necessary. The study in this paper validates guidelines from analysis, with a simulation that implements all layers of the Internet protocol stack. The results show that as the source-destination channel becomes more degraded, both Amplify-and-Forward and Decode-and-Forward cooperation yield a TCP performance better than non-cooperative scheme. This is even considering that the two-phase operation of cooperative communications reduces the effective capacity. The issue of reduced capacity is resolved with cross-layer schemes, which result in improved performance at the cost of added complexity to implement the cross-layer mechanisms and to dynamically schedule the transmission of the cooperating node.

A key challenge in the design of real-time wireless multimedia systems is the presence of fading coupled with strict delay constraints. A very effective answer to this problem is the use of diversity achieving techniques to overcome the fading nature of the wireless channels caused by the mobility of the nodes. The mobility of the nodes gives rise to the need of cooperation among the nodes to enhance the system performance. This paper focuses on comparing systems that exhibit diversity of three forms: source coding diversity, channel coding diversity, and user cooperation diversity implemented through multihop or relay channels with amplify-and-forward or decode-and-forward protocols. Commonly used in multimedia communications, performance is measured in terms of the distortion exponent, which measures the rate of decay of the end-to-end distortion at asymptotically high signal-to-noise ratio (SNR). For the case of repetition coding at the relay nodes, we prove that having more relays is not always beneficial. For the general case of having a large number of relays that can help the source using repetition coding, the optimum number of relay nodes that maximizes the distortion exponent is determined in this paper. This optimum number of relay nodes will depend on the system bandwidth as well as the channel quality. The derived result shows a trade-off between the quality (resolution) of the source encoder and the amount of cooperation (number of relay nodes). Also, the performances of the channel coding diversity-based scheme and the source coding diversity-based scheme are compared. The results show that for both relay and multihop channels, channel coding diversity provides the best performance, followed by the source coding diversity.

WiMAX is an emerging and powerful technology in broadband wireless communications in that it can simultaneously provide high-speed broadband services over large distances. However, signal distortion due to channel fading, noise, and Doppler can limit the overall transmission data rate and coverage. To minimize the impact, channel estimation must be performed to remove the effects of the channel. In this paper, we present uplink channel estimation algorithms for WiMAX PUSC and AMC and analyze their performance under different channel conditions. Our results show that the performance of each algorithm depends largely on the channel delay spread and signal-to-noise ratio.

A novel cooperative multiple access protocol for packet speech communications is proposed, where cooperation is achieved through the deployment of a relay node that exploits the silence periods typical of speech communications. The relay forwards speech packets for active calls using a subset of the free time slots left available by users that are silent. No new channel resources are needed for cooperation and the system encounters no bandwidth losses. Because the resources allocated to the relay are not drawn from the pool of reused resources but from those potentially used for random channel access. Thus, the use of cooperation introduces a tradeoff between the amount of help offered to active calls and the probability of a successful contention for channel access. Such cooperation tradeoff is investigated and guidelines for the choice of protocol parameters are developed. The throughput and delay performance of the proposed protocol are characterized and compared to a similar non-cooperative packet speech protocol. Results demonstrate significant gains achieved by the proposed cooperative protocol. Moreover, the speech quality under the cooperative protocol was measured using a perceptual model, and results reveal significant improvement over the non-cooperative protocol especially in the low signal-to-noise ratio regime.

Diversity techniques are an effective answer to the challenges presented by fading channels. This paper focuses on studying the performance of systems with diversity of three forms: source coding diversity, channel coding diversity, and user-cooperation diversity. To best reflect a focus on real-time multimedia communications, performance is measured through the distortion exponent, which measures the rate of decay of the end-to-end distortion at high SNRs. User-cooperation diversity takes the form of a relay channel implemented with amplify-and-forward processing at the relay. The results show that channel coding diversity provides the best performance, followed by source coding diversity. The results also show a tradeoff between the quality (resolution) of the source encoder and the amount of cooperation (number of relay nodes).

The study of joint source-channel coding (JSCC) systems faces one major challenge in obtaining an analytical expression for the function that links end-to-end distortion with channel signal-to-noise ratio, the D-SNR curve. In this paper, for certain multimedia systems using practical source and channel codes in a JSCC bit rate allocation design, the D-SNR curve is shown to be well approximated by a set of carefully selected points where the relative contribution of channel errors to end-to-end distortion is small. This approach has the potential advantage that it could be applied to represent performance of many practical systems using JSCC bit rate allocation for which it is shown that the D-SNR function is approximately linear in log-log scales. A unified framework for the modeling, analysis and performance measurement of these systems is proposed by considering a view of diversity more general than its usual interpretation. This view extends that of diversity to include redundant information so coding and diversity gain are still used to characterize performance. Furthermore, the proposed approach is applied to study issues arising from using practical source and channel codes, including the effects on performance of channel codes of different strength or source codes with different compression efficiency.

Transmit power limitations and quality-impairing channels present key challenges to wireless communications. A possible solution to these problems is the application of user-cooperation techniques so as to improve link quality. This paper studies the tradeoffs involved in combining user cooperation with practical source and channel coding in systems featuring rate-adaptive source and channel coding of conversational traffic. Performance is measured through the D-SNR curve, which measures the relation between end-to-end distortion and channel signal-to-noise ratio (SNR). The D-SNR curve is accurately characterized as a linear function in log-log scales. Also, it is shown that the tradeoffs involved in combining amplify-and-forward or decode-and-forward cooperation with source and channel coding translates into cooperative schemes showing a decrease in distortion at approximately half the rate as non-cooperative schemes but with larger coding gain. Because of this, the studied non-cooperative schemes show better performance only at high SNR. In addition, the D-SNR characterization is used to compare amplify-and-forward and decode-and-forward cooperation for channel codes of different strength and to study the effects of source codec efficiency, where it is shown that diversity gain is reduced proportionally to the source codec loss of efficiency.

A novel cooperative multiple access protocol for packet speech communications is proposed. Cooperation is achieved through a relay node and by exploiting the silence periods during speech communication. The relay forwards packets for the active calls during some of the time slots that are free from those users which are silent. Therefore, no extra channel resources are needed for cooperation and the system encounters no bandwidth losses. A Markov model characterizing the network operation is built and thoroughly analyzed. The throughput and delay performance of the proposed protocol are characterized and compared to a similar non-cooperative protocol for speech communications.

This paper studies the function that links end-to-end distortion with channel signal-to-noise ratio, the D-SNR curve, for systems using Joint Source-Channel Coding (JSCC) bit rate allocation. The D-SNR curve is shown to be well approximated for certain multimedia systems using practical source and channel codes, by a linear function in log-log scales. The D-SNR curve is characterized by following an approach that considers a set of carefully selected points, which are those where the relative contribution of channel errors to end-to-end distortion is small. The D-SNR characterization is applied to study the effects on performance of channel codes of different strength or source codes with different compression efficiency. The approach followed to characterize the D-SNR curve has the potential advantage that it could be applied to represent performance of many practical systems using JSCC bit rate allocation, as it is illustrated for a scheme carrying voice traffic.

The performance limits of multimedia systems combining source (multiple description) coding and channel coding with user cooperation diversity over multi-hop channels is studied. Performance is measured through the distortion exponent, which measures the rate of decay of the end-to-end distortion at asymptotic high SNRs. Two implementations for user cooperation are considered: amplify-and-forward and decode-and-forward. Results comparing different source and channel coding schemes show that optimum channel coding diversity provides the best performance, followed by source coding diversity. The results also show that at low bandwidth expansion factor, source encoding distortion is the main limiting factor. As the bandwidth expansion factor increases, user cooperation diversity is the main limiting factor, thus, the distortion exponent could be improved by increasing the number of relays.

The study of joint source-channel Coding (JSCC) systems faces one major challenge in obtaining an analytical expression for the function that links end-to-end distortion with channel signal-to-noise ratio, the D-SNR curve. In this paper, for certain multimedia systems using practical source and channel codes in a JSCC bit rate allocation design, the D-SNR curve is shown to be well approximated by a set of carefully selected points where the relative contribution of channel errors to end-to-end distortion is small. This approach has the potential advantage that it could be applied to represent the performance of many practical systems using JSCC bit rate allocation for which it is shown that the D-SNR function is approximately linear in log-log scales. A unified framework for the modeling, analysis, and performance measurement of these systems is proposed by considering a view of diversity more general than its usual interpretation. This view extends that of diversity to include redundant information so that coding and diversity gain are still used to characterize performance. Furthermore, the proposed approach is applied to study issues arising from using practical source and channel codes, including the effects on the performance of channel codes of different strength or source codes with different compression efficiency.

This paper studies the transmission of images encoded using an embedded source encoder over a wireless network allowing user cooperation. A dynamic programming algorithm is applied to optimally allocate to each source coded packet error protection in the form of a choice of channel code and a decision on the use of cooperation. The results show that for degraded source-destination channels, the use of user cooperation on all source coded packets significantly improves the reconstructed quality. As the source-destination channel improves the optimal policy becomes a hybrid that uses user cooperation only for the most important source packets. When the source destination channel is sufficiently good, all source packets are sent without cooperation. Thus, a test is presented to estimate the channels states when cooperation is first used.

Cooperative diversity exploits the broadcast nature of wireless channels by allowing users to relay information for each other so as to create multiple signal paths. This technique could be used together with joint source-channel bit rate allocation to transmit conversational multimedia traffic. This paper studies, following a methodology that avoids the use of high or low SNR approximations, the interaction between joint source-channel bit rate allocation with AF and DF cooperation. Furthermore, the effect of QoS constraints on performance is studied. In addition to the advantages of user-cooperation at medium and low source-destination channel signal-to-noise ratio, the results in this paper point at the fact that significant extra performance gains could be obtained by careful selection of the relay node. Guidelines for choosing the relay are also discussed.

In downlink of code-division multiple-access (CDMA) networks, the maximal number of real-time calls can be increased by smoothly increasing the end-to-end distortions. In this paper, a cross-layer optimization system is developed to control each user's distortion by adapting source coding rates, channel coding rates, and transmit powers. In addition, the channel-induced distortion is controlled to be only a small proportion of the total end-to-end distortion, such that the subjective quality of the received signal is high. The formulated problem is to reduce the overall end-to-end distortion in downlink single-cell systems, under the constraints of users' maximal acceptable distortions and maximal total transmit power from the base station. To solve this problem, a near-optimal algorithm is constructed to allocate resources. A performance upper bound is developed and compared with the performance of the proposed algorithm. A dynamic system considering speech activities and different offered loads is also analyzed. From the simulation results, the proposed algorithm significantly reduces distortion and the necessary maximal transmit power when the number of users is large, compared with the traditional voice over CDMA schemes.

Transmitting multiple real-time encoded videos to multiple users over wireless cellular networks is a key driving force for developing broadband technology. We propose a new framework to transmit multiple users' video programs encoded by MPEG-4 FGS codec over downlink multicode CDMA networks in real time. The proposed framework jointly manages the rate adaptation of source and channel coding, CDMA code allocation, and power control. Subject to the limited system resources, such as the number of pseudo-random codes and the maximal power for CDMA transmission, we develop an adaptive scheme of distortion management to ensure baseline video quality for each user and further reduce the overall distortion received by all users. To efficiently utilize system resources, the proposed scheme maintains a balanced ratio between the power and code usages. We also investigate three special scenarios where demand, power, or code is limited, respectively. Compared with existing methods in the literature, the proposed algorithm can reduce the overall system's distortion by 14% to 26%. In the demand-limited case and the code-limited but power-unlimited case, the proposed scheme achieves the optimal solutions. In the power-limited but code-unlimited case, the proposed scheme has a performance very close to a performance upper bound

Cooperative diversity exploits the broadcast nature of wireless channels by allowing users to relay information for each other so as to create multiple signal paths. This paper analyzes what is the best strategy from the viewpoint of a resource allocation protocol, to match source coding with cooperation diversity for conversational multimedia communications by studying the distortion performance for different schemes. The results show that the best performance is obtained when all layers of a layered-coded source are sent with user cooperation (using decode-and-forward in most cases) if the source-destination channel is bad, and with no user cooperation, if the source-destination channel is good. The results also show that the gains from cooperative diversity outweigh the loss due to the sacrifice in overall bandwidth and that cooperation performance is sensitive to the proportion of communication capacity allocated for cooperation.

In this paper, a protocol is designed to manage source rate/channel coding rate adaptation, code allocation, and power control to transmit real-time MPEG-4 FGS video over downlink multicode CDMA networks. We develop a fast adaptive scheme of distortion management to reduce the overall distortion received by all users subject, to the limited number of codes and maximal transmitted power. Compared with a modified greedy method in literature, our proposed algorithm can reduce the overall system's distortion by at least 45%.

In CDMA, resource allocation is a task critical to the performance of this inherently interference limited multiple access technique. This paper also presents the solution to the problem of optimal resource allocation to resolve interference-generated congestion for an arbitrary set of real-time source encoders and shows that this problem could be viewed as the one of statistical multiplexing in source-adapted CDMA. Based on this, we develop optimal algorithms to solve the allocation problem. Simulations using MPEG4 FGS video shows that the proposed systems significantly outperforms systems with no adaptation, being able to support more than three times the number of calls while the quality degrades gracefully.

In CDMA networks it is possible to increase the maximum number of users of real time applications by smoothly increasing each end-to-end distortion. We study a protocol for downlink CDMA that allocates source coding rate, channel coding rate and transmitted power based on each user's channel state. The allocation of resources is performed with the constraints of users' maximum distortion and base station's maximum transmitted power in such a way that users operate under carefully controlled distortions. The optimization goal is to minimize the overall distortion in downlink single-cell systems. When the system is highly loaded, the idea for the proposed solution is to initialize the resource allocation with that corresponding to maximum distortion for all users, and then incrementally allocate the remaining transmitted power quota to the user that, at each step, can reduce the distortion with the least use of power. We show that this user must have a high distortion, experience a good channel condition, or generate small interference. We also extend our study to include speech's talk spurt-silence nature and to consider a dynamic model with different offered loads. From simulation results, the proposed algorithm fundamentally reduces the distortions and the necessary maximum transmitted power when the number of users is large, compared with a traditional CDMA scheme (with no distortion control).

In CDMA, resource allocation is a task critical to the performance of this inherently interference limited multiple access technique. In this paper we introduce a new technique aimed at increasing the number of real-time calls supported in a CDMA network at the cost of a smooth controllable degradation of reconstructed source quality while channel-induced distortion remains bounded by fixing a maximum target FER. This paradigm is based on real-time source codecs with externally adaptable output rate. This work also includes a study of the relation between interference, the number of users in the network and the reconstructed source quality at the output of the source decoder for the case of a single-state real-time coder. We present mathematical analysis and simulations to show that it is possible to achieve a 30% relative increase in the number of users for a 10% relative increase in distortion and to significantly outperform an equivalent CDMA system in the relative increase in the number of users that can be achieved for a given increase in source distortion.

We present a joint source-channel coding scheme based on incremental redundancy and feedback for transmission of real-time sources over wireless channels under strict delay constraints. The proposed scheme operates at constant bit rate and delay so as to capture the benefits of a feedback channel, while keeping the synchronous nature of pure forward error correction systems. We formulate the underlying Markov chain by introducing the notion of codetype and present a design algorithm for channel and source rate allocation. We present simulation results for speech transmission and show gains of up to 1 dB over pure FEC systems. We also present an application to CDMA networks and show increases of up to 28 % in the number of calls that can be simultaneously supported.

In multiple access wireless networks with co-channel interference, allocating resources such as transmitted powers and source rates is a task critical to improve performance. In this paper, we introduce a new technique aimed at minimizing the overall transmitted power subject to constraints on the incurred source distortion. The technique is based on the use of real-time source codecs with externally adaptable output rate and rate compatible punctured convolutional (RCPC) channel encoders. We develop an adaptive algorithm to find the optimal power and source rate allocation to the different users according to their channel conditions and under distortion constraints. We present simulation results to show that it is possible to reduce the overall transmitted power significantly with a relatively small distortion increases for some users, and while keeping the network average distortion unchanged.