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Recently, the capacity region of a multiple-input multiple-output (MIMO) Gaussian broadcast channel, with Gaussian codebooks and known-interference cancellation through dirty paper coding, was shown to equal the union of the capacity regions of a collection of MIMO multiple-access channels. We use this duality result to evaluate the system capacity achievable in a cellular wireless network with multiple antennas at the base station and multiple antennas at each terminal. Some fundamental properties of the rate region are exhibited and algorithms for determining the optimal weighted rate sum and the optimal covariance matrices for achieving a given rate vector on the boundary of the rate region are presented. These algorithms are then used in a simulation study to determine potential capacity enhancements to a cellular system through known-interference cancellation. We study both the circuit data scenario in which each user requires a constant data rate in every frame and the packet data scenario in which users can be assigned a variable rate in each frame so as to maximize the long-term average throughput. In the case of circuit data, the outage probability as a function of the number of active users served at a given rate is determined through simulations. For the packet data case, long-term average throughputs that can be achieved using the proportionally fair scheduling algorithm are determined. We generalize the zero-forcing beamforming technique to the multiple receive antennas case and use this as the baseline for the packet data throughput evaluation.

In this paper, we spotlight vehicle-to-everything (V2X) communications in 5G cellular networks. Cellular V2X (C-V2X) communications in 5G enable more advanced services with requirements of ultra-low latency and ultra-high reliability. How to make full use of the limited physical-layer resources is a key determinant to guarantee the quality of service (QoS). Therefore, resource allocation plays an essential role in exchanging information between vehicles, infrastructure, and other devices. In order to intelligently and reasonably allocate resources, a self-adaptive fuzzy logic-based strategy is developed in this paper. To evaluate the network performance for this adaptive strategy, a system model for V2X communications is built for urban areas, and typical safety and non-safety services are deployed in the network. Simulation results reveal that the proposed fuzzy logic-based algorithm can substantially improve resource utilization and satisfy the requirements of V2X services, compared with prior counterparts, which cannot provide guaranteed services due to low resource utilization.

Ultra-narrowband (UNB) communications has become a signature feature for many emerging low-power wide-area (LPWA) networks. Specifically, using extremely narrowband signals helps the network connect more Internet-of-things (IoT) devices within a given band. It also improves robustness to interference, extending the coverage of the network. In this paper, we study the coexistence capability of UNB networks and their scalability to enable massive access. To this end, we develop a stochastic geometry framework to analyze and model UNB networks on a large scale. The framework captures the unique characteristics of UNB communications, including the asynchronous time-frequency access, signal repetition, and the absence of base station (BS) association. Closed-form expressions of the transmission success probability and network connection density are presented for several UNB protocols. We further discuss multiband access for UNB networks, proposing a low-complexity protocol. Our analysis reveals several insights on the geographical diversity achieved when devices do not connect to a single BS, the optimal number of signal repetitions, and how to utilize multiple bands without increasing the complexity of BSs. Simulation results are provided to validate the analysis, and they show that UNB communications enables a single BS to connect thousands of devices even when the spectrum is shared with other networks., This paper is accepted for publication in the IEEE Journal on Selected Areas in Communications. arXiv admin note: text overlap with arXiv:1811.11092

Content delivery networks (CDNs) distribute much of the Internet content by caching and serving the objects requested by users. A major goal of a CDN is to maximize the hit rates of its caches, thereby enabling faster content downloads to the users. Content caching involves two components: an admission algorithm to decide whether to cache an object and an eviction algorithm to determine which object to evict from the cache when it is full. In this paper, we focus on cache admission and propose a novel algorithm called RL-Cache that uses model-free reinforcement learning (RL) to decide whether or not to admit a requested object into the CDN’s cache. Unlike prior approaches that use a small set of criteria for decision making, RL-Cache weights a large set of features that include the object size, recency, and frequency of access. We develop a publicly available implementation of RL-Cache and perform an evaluation using production traces for the image, video, and web traffic classes from Akamai’s CDN. The evaluation shows that RL-Cache improves the hit rate in comparison with the state of the art and imposes only a modest resource overhead on the CDN servers. Further, RL-Cache is robust enough that it can be trained in one location and executed on request traces of the same or different traffic classes in other locations of the same geographic region. The paper also reports extensive analyses of the RL-Cache sensitivity to its features and hyperparameter values. The analyses validate the made design choices and reveal interesting insights into the RL-Cache behavior. pub

This paper proposes interference mitigation techniques for provisioning ultrareliable low-latency wireless communication in an industrial automation setting, where multiple transmissions from controllers to actuators interfere with each other. Channel fading and interference are key impairments in wireless communication. This paper leverages the recently proposed ``Occupy CoW'' protocol that efficiently exploits the broadcast opportunity and spatial diversity through a two-hop cooperative communication strategy among distributed receivers to combat deep fading, but points out that because this protocol avoids interference by frequency division orthogonal transmission, it is not scalable in terms of bandwidth required for achieving ultrareliability, when multiple controllers simultaneously communicate with multiple actuators (akin to the downlink of a multicell network). The main observation of this paper is that full frequency reuse in the first phase, together with successive decoding and cancellation of interference, can improve the performance of this strategy notably. We propose two protocols depending on whether interference cancellation or avoidance is implemented in the second phase, and show that both outperform Occupy CoW in terms of the required bandwidth and power for achieving ultrareliability at practical values of the transmit power.

5G wireless networks are expected to support Ultra Reliable Low Latency Communications (URLLC) traffic which requires very low packet delays ( < 1 msec.) and extremely high reliability ($\sim$99.999\%). In this paper we focus on the design of a wireless system supporting downlink URLLC traffic. Using a queuing network based model for the wireless system we characterize the effect of various design choices on the maximum URLLC load it can support, including: 1) system parameters such as the bandwidth, link SINR , and QoS requirements; 2) resource allocation schemes in Orthogonal Frequency Division Multiple Access (OFDMA) based systems; and 3) Hybrid Automatic Repeat Request (HARQ) schemes. Key contributions of this paper which are of practical interest are: 1) study of how the the minimum required system bandwidth to support a given URLLC load scales with associated QoS constraints; 2) characterization of optimal OFDMA resource allocation schemes which maximize the admissible URLLC load; and 3) optimization of a repetition code based HARQ scheme which approximates Chase HARQ combining.

Owing to the explosive growth of requirements of rapid emergency communication response and accurate observation services, airborne communication networks (ACNs) have received much attention from both industry and academia. ACNs are subject to heterogeneous networks that are engineered to utilize satellites, high-altitude platforms (HAPs), and low-altitude platforms (LAPs) to build communication access platforms. Compared to terrestrial wireless networks, ACNs are characterized by frequently changed network topologies and more vulnerable communication connections. Furthermore, ACNs have the demand for the seamless integration of heterogeneous networks such that the network quality-of-service (QoS) can be improved. Thus, designing mechanisms and protocols for ACNs poses many challenges. To solve these challenges, extensive research has been conducted. The objective of this special issue is to disseminate the contributions in the field of ACNs. To present this special issue with the necessary background and offer an overall view of this field, three key areas of ACNs are covered. Specifically, this paper covers LAP-based communication networks, HAP-based communication networks, and integrated ACNs. For each area, this paper addresses the particular issues and reviews major mechanisms. This paper also points out future research directions and challenges.

The performance of cloud radio access network (C-RAN) is limited by the finite capacities of the backhaul links connecting the centralized processor (CP) with the base-stations (BSs), especially when the backhaul is implemented in a wireless medium. This paper proposes the use of wireless multicast together with BS caching, where the BSs pre-store contents of popular files, to augment the backhaul of C-RAN. For a downlink C-RAN consisting of a single cluster of BSs and wireless backhaul, this paper studies the optimal cache size allocation strategy among the BSs and the optimal multicast beamforming transmission strategy at the CP such that the user's requested messages are delivered from the CP to the BSs in the most efficient way. We first state a multicast backhaul rate expression based on a joint cache-channel coding scheme, which implies that larger cache sizes should be allocated to the BSs with weaker channels. We then formulate a two-timescale joint cache size allocation and beamforming design problem, where the cache is optimized offline based on the long-term channel statistical information, while the beamformer is designed during the file delivery phase based on the instantaneous channel state information. By leveraging the sample approximation method and the alternating direction method of multipliers (ADMM), we develop efficient algorithms for optimizing cache size allocation among the BSs, and quantify how much more cache should be allocated to the weaker BSs. We further consider the case with multiple files having different popularities and show that it is in general not optimal to entirely cache the most popular files first. Numerical results show considerable performance improvement of the optimized cache size allocation scheme over the uniform allocation and other heuristic schemes., Accepted and to appear in IEEE Journal on Selected Areas in Communications, Special Issue on Caching for Communication Systems and Networks

In this paper, we cope with the reliable and efficient data transfer problem in aeronautical ad hoc networks (AANETs). AANETs are different from terrestrial ad hoc networks and these distinctions feature AANETs with large propagation delay, highly dynamic network topology, and high error probability, which pose many new challenges for data transfer in such environments. In this paper, we propose a protocol, called FRUDP, which combines reliable UDP and fountain code to achieve reliable and efficient data transfer in AANETs. It employs Raptor codes to recover from data losses to mitigate retransmission caused by high channel losses in AANETs. A code rate determining algorithm is developed to estimate the redundancy on the fly by taking into full consideration the time-varying aeronautical network conditions. Moreover, the improved selective negative acknowledgment scheme is utilized to solve the bandwidth asymmetry problem in AANETs and a congestion control scheme is deployed to decouple congestion decisions from packet losses in order to avoid the erroneous congestion decisions due to frequent link handoffs. The proposed FRUDP is fully implemented directly on top of UDP in Linux and examined over a variety of emulation network environments. The experimental results show that FRUDP is suitable for reliable and efficient data transfer service in AANETs.

Non-orthogonal multiple access (NOMA) has been considered as a highly efficient communication technology in the fifth generation (5G) networks by serving multiple users concurrently through non-orthogonal sharing communication resources. NOMA can be combined with both massive multiple input multiple output (MIMO) and relaying technologies to further improve 5G system efficiency at the cost of increased complexity. These combinations rely on the efficient utilization of 3-D communication resources. In the first part of this paper, we investigate highly efficient 3-D resource allocation for massive MIMO-NOMA systems. Due to hardware complexity constraints and channel variation in the massive MIMO-NOMA system, efficient antenna selection and user scheduling algorithms are proposed for sum rate maximization. In the second part of this paper, a collaborative NOMA-assisted relaying (CNAR) system is proposed to serve multiple cell-edge users by 3-D resource utilization. To reduce the relaying complexity in CNAR system, a simplified-CNAR (S-CNAR) system is proposed as an alternative NOMA-enabled relaying strategy. Numerical results show that our antenna selection and user scheduling algorithms achieve similar performance to existing methods with reduced complexity. Under high target rate, CNAR obtains better performance over other transmission strategies and S-CNAR reaches similar performance by simplified relaying scheme.

To address the ever increasing high data rate and connectivity requirements in the next generation 5G wireless network, novel radio access technologies (RATs) are actively explored to enhance the system spectral efficiency and connectivity. As a promising RAT for 5G cellular networks, non-orthogonal multiple access (NOMA) has attracted extensive research attentions. Compared with the orthogonal multiple access (OMA) that has been widely applied in existing wireless communication systems, NOMA possesses the potential to further improve the system spectral efficiency and connectivity capability. This paper develops analytical frameworks for NOMA downlink and uplink multi-cell wireless systems to evaluate the system outage probability and average achievable rate. In the downlink NOMA system, two different NOMA group pairing schemes are considered, based on which theoretical results on outage and achievable data rates are derived. In the uplink NOMA, revised back-off power control scheme is applied, and outage probability and per UE average achievable rate are derived. As wireless networks turn into more and more densely deployed, inter-cell interference has become a dominant capacity limiting factor but has not been addressed in most of the existing NOMA studies. In this paper, a stochastic geometry approach is used to model a dense wireless system, that supports NOMA on both uplink and downlink, based on which analytical results are derived either in pseudo-closed forms or succinct closed forms and are further validated by simulations. Numerical results demonstrate that NOMA can bring considerable system-wide performance gain compared with OMA on both uplink and downlink when properly designed.

The millimeter wave (mmWave) bands offer the possibility of orders of magnitude greater throughput for fifth generation (5G) cellular systems. However, since mmWave signals are highly susceptible to blockage, channel quality on any one mmWave link can be extremely intermittent. This paper implements a novel dual connectivity protocol that enables mobile user equipment (UE) devices to maintain physical layer connections to 4G and 5G cells simultaneously. A novel uplink control signaling system combined with a local coordinator enables rapid path switching in the event of failures on any one link. This paper provides the first comprehensive end-to-end evaluation of handover mechanisms in mmWave cellular systems. The simulation framework includes detailed measurement-based channel models to realistically capture spatial dynamics of blocking events, as well as the full details of MAC, RLC and transport protocols. Compared to conventional handover mechanisms, the study reveals significant benefits of the proposed method under several metrics., 16 pages, 13 figures, to appear on the 2017 IEEE JSAC Special Issue on Millimeter Wave Communications for Future Mobile Networks

Leveraging multiple simultaneous small cell connections is an emerging and promising solution to enhance session continuity in millimeter-wave (mmWave) cellular systems that suffer from frequent link interruptions due to blockage in ultra-dense urban deployments. However, the available performance benefits of feasible multi-connectivity strategies as well as the tentative service quality gains that they promise remain an open research question. Addressing it requires the development of a novel performance evaluation methodology, which should consider: 1) the intricacies of mmWave radio propagation in realistic urban environments; 2) the dynamic mmWave link blockage due to human mobility; and 3) the multi-connectivity network behavior to preserve session continuity. In this paper, we construct this much needed methodology by combining the methods from queuing theory, stochastic geometry, as well as ray-based and system-level simulations. With this integrated framework, both user- and network-centric performance indicators together with their underlying scaling laws can be quantified in representative mmWave scenarios. To ensure modeling accuracy, the components of our methodology are carefully cross verified and calibrated against the current considerations in the standards. Building on this, a thorough comparison of alternative multi-connectivity strategies is conducted, as this paper reveals that even simpler multi-connectivity schemes bring notable improvements to session-level mmWave operation in realistic environments. These findings may become an important reference point for subsequent standardization in this area.

To support the multi-gigabit per second data rates of 5G wireless networks, there have been significant efforts on the research and development of massive MIMO (M-MIMO) technologies at the physical layer. So far, however, the understanding of how M-MIMO could affect the performance of network control, and optimization algorithms remain rather limited. In this paper, we focus on analyzing the performance of the queue-length-based joint congestion control and scheduling framework over M-MIMO cellular networks with limited channel state information (CSI). Our contributions in this paper are twofold. First, we characterize the scaling performance of the queue-lengths and show that there exists a phase transitioning phenomenon in the steady-state queue-length deviation with respect to the CSI quality (reflected in the number of bits $B$ that represent CSI). Next, we characterize the congestion control rate scaling performance and show that there also exists a phase transitioning phenomenon in steady-state congestion control rate deviation with respect to the CSI quality. Collectively, the findings in this paper advance our understanding of the tradeoffs between delay, throughput, and the accuracy/complexity of CSI acquisition in M-MIMO cellular network systems.

Keystroke privacy is critical for ensuring the security of computer systems and the privacy of human users as what is being typed could be passwords or privacy sensitive information. In this paper, we show for the first time that WiFi signals can also be exploited to recognize keystrokes. The intuition is that while typing a certain key, the hands and fingers of a user move in a unique formation and direction and thus generate a unique pattern in the time-series of channel state information (CSI) values, which we call CSI-waveform for that key. In this paper, we propose a WiFi signal-based keystroke recognition system called WiKey. WiKey consists of two commercial off-the-shelf WiFi devices, a sender (such as a router) and a receiver (such as a laptop). The sender continuously emits signals and the receiver continuously receives signals. When a human subject types on a keyboard, WiKey recognizes the typed keys based on how the CSI values at the WiFi signal receiver end. We implemented the WiKey system using a TP-Link TL-WR1043ND WiFi router and a Lenovo X200 laptop. WiKey achieves over 97.5% detection rate for detecting the keystroke and 96.4% recognition accuracy for classifying single keys. In real-world experiments, WiKey can recognize keystrokes in a continuously typed sentence with an accuracy of 93.5%. WiKey can also recognize complete words inside a sentence with over 85% accuracy.

Visible light communication (VLC) has been shown to have several advantages over traditional wireless communication. In this paper, we envision an LED-light-to-smartphone VLC protocol for delivering messages to a group of randomly arriving smartphone receivers. Our goal is to increase the throughput for large message delivery, as well as to reduce the delay of message broadcast. Key challenges for implementing such a VLC message broadcast protocol are: 1) the imperfect synchronization among receivers and the transmitter; 2) the receivers’ arbitrary arrival times; and 3) the diversity of receivers’ smartphones (e.g., location, capability, and frame-rates). In this paper, we propose a new modulation scheme and design link-layer protocols for improving the network data rate. We carefully design and implement our protocol, Martian, which allows smooth communication from the LED lights to a group of smartphone embedded cameras. Across several phone models, Martian can achieve data rate of about 1.6 kb/s even with NLOS -light. It also has a stable and small delay for broadcasting messages to the randomly arriving receivers.

The market uptake of the 4th Generation networks is expected to support the increasing demand for wireless broadband services and ensure an enhanced mobile user experience. In this direction, the convergence of a wireless access network with an optical backhauling has been proposed. However, in such a converged architecture, the traditional fixed commitment of the backhaul resources does not prove to be as efficient, and novel dynamic schemes are required that consider both the needs of the base stations and the limitations of the passive optical network. This paper is concerned with the topic of resource allocation in two competing base stations that belong to different operators and share a common optical backhaul network infrastructure. An approach based on evolutionary game theory is proposed and employed, with a view to examining the interactions among the base stations and the passive optical network. Using the model of replicator dynamics, the proposed system design is proved to be asymptotically stable. In addition, this paper studies and reveals the extent to which time delay can have an impact on the proposed system design.

Continued scaling of switching capacity in the Internet core is threatened by power considerations. Internet service providers face increased carbon footprint and operational costs, while router manufacturers encounter upper limits on switching capacity per rack. This paper studies the role of packet buffer memory on the power consumption of backbone routers. Our first contribution is to estimate from published datasheets the energy costs of static RAM/dynamic RAM packet-buffer memory, showing that it accounts for over 10% of power consumption in a typical router line-card; we then show, using empirical data from core and enterprise networks, that much of this memory is used for only a small fraction of time. Our second contribution is to develop a simple yet practical algorithm for putting much of the memory components to sleep and waking them as needed, while being able to control resulting traffic performance degradation in the form of packet loss during transient congestion. Finally, we conduct a comprehensive evaluation of our scheme, via analytical models pertaining to long-range-dependent traffic, using simulations of offline traffic traces taken from carrier/enterprise networks as well as online Transmission Control Protocol flows in ns2, and by implementing our scheme on a programmable-router test bed. This paper is the first to show the feasibility of, and energy savings from, dynamic management of packet buffer memory in core routers in the market today.

This paper presents innovative back-channel wireless communication techniques for ultra-low power (ULP) devices. The concept of embedded back-channel communication is proposed to enable a variety of new applications by inter-connecting heterogeneous ULP devices through existing orthogonal frequency division multiplexing (OFDM)-based WiFi (IEEE 802.11a/g/n/ac) networks. The proposed back-channel communication allows ULP devices to decode messages embedded in WiFi OFDM packets even if these ULP devices are incapable of demodulating OFDM. The proposed back-channel signaling has unique properties that are easily detectable by non-WiFi ULP receivers consuming sub- $mW$ of active power. The proposed scheme eliminates the need for specialized transmitter hardware or dedicated channel resources for embedded back-channel signal transmission. Instead, carefully sequenced data bit streams will generate back-channel messages from already-deployed WiFi infrastructure without any hardware modification. This paper demonstrates that WiFi OFDM back-channel communication is feasible in various modulation formats, such as pulse position modulation, pulse phase shift keying, or frequency shift keying. Systematic algorithms are unveiled to create back-channel messages in various modulation formats from a WiFi standard compliant datapath. Comprehensive bit error rate performance analysis of various WiFi back-channel communication schemes is derived and validated in realistic multi-path frequency selective fading channels.

In this paper, we consider a multiuser multiple-input multiple-output (MIMO) decode-and-forward (DF) relay broadcasting channel (BC) with single source, multiple energy harvesting (EH) relays, and multiple destinations. All the nodes are equipped with multiple antennas. The EH and information decoding tasks at the relays and destinations are separated over the time, which is termed as the time switching scheme. As optimal solutions for the sum-rate maximization problems of BC channels and the MIMO interference channels are hard to obtain, the end-to-end sum rate maximization problem of a multiuser MIMO DF relay BC channel is even harder. In this paper, we propose to tackle a simplified problem, where we employ the block diagonalization (BD) procedure at the source, and we mitigate the interference between the relay-destination channels using an algorithm similar to the BD method. In order to show the relevance of our low complex proposed solution, we compare it with the minimum mean-square error (mmse) solution that was shown in the literature to be equivalent to the solution of the sum-rate maximization in the MIMO broadcasting interfering channels. We also investigate the time division multiple access (TDMA) solution, which separates all the information transmissions from the source to the relays and from the relays to the destinations over time. We provide the numerical results to show the relevance of our proposed solution, in comparison with the no co-channel interference case, the TDMA-based solution, and the mmse-based solution.

Ambient radio frequency (RF) energy harvesting methods have drawn significant interests due to their ability to provide energy to wireless devices from ambient RF sources. This paper considers ambient RF energy harvesting wireless sensor networks where a sensor node transmits data to a data sink using the energy harvested from the signals transmitted by the ambient RF sources. We analyze the performance of the network, i.e., the mean of the harvested energy, the power outage probability, and the transmission outage probability. In many practical networks, the locations of the ambient RF sources are spatially correlated and the ambient sources exhibit repulsive behaviors. Therefore, we model the spatial distribution of the ambient sources as an $\alpha $ -Ginibre point process ( $\alpha $ -GPP), which reflects the repulsion among the RF sources and includes the Poisson point process as a special case. We also assume that the fading channel is Nakagami- $m$ distributed, which also includes Rayleigh fading as a particular case. In this paper, by exploiting the Laplace transform of the $\alpha $ -GPP, we introduce semi-closed-form expressions for the considered performance metrics and provide an upper bound of the power outage probability. The derived expressions are expressed in terms of the Fredholm determinant, which can be computed numerically. In order to reduce the complexity in computing the Fredholm determinant, we provide a simple closed-form expression for the Fredholm determinant, which allows us to evaluate the Fredholm determinant much more efficiently. The accuracy of our analytical results is validated through simulation results.

Spectrum sharing and aggregation among authorized secondary users (A-SUs) are important tasks in operating effective cognitive radio networks. Furthermore, in protecting spectrum sharing/aggregation against unauthorized secondary users (UA-SUs), secondary user access control (SUAC) is needed, which is investigated in this paper. A jamming signal is injected to degrade the spectrum sensing performance of UA-SUs, while reliable spectrum sensing performance for A-SUs can be achieved through an oblique projection-based jamming cancellation method. An orthogonal frequency division multiplexing-based transmission model is considered in this paper. The generalized likelihood ratio test algorithm is used for both authorized and unauthorized SUs in spectrum sensing. Numerical results show the effectiveness of the proposed SUAC in degrading the spectrum sensing performance of the unauthorized SUs.

Licensed-assisted access (LAA), which conveys data information via both licensed and unlicensed bands through spectrum aggregation, becomes a promising solution to enhance the capacity of wireless systems. In view of the potential impact on the incumbent system operating in unlicensed bands, the medium access control (MAC) protocol design for LAA system to harmonically coexist with its neighboring incumbent users is one of the most critical and challenging issues. In this paper, we consider a long-term evolution-based LAA (LAA-LTE) system operating in the WiFi unlicensed spectrum, for which the listen-before-talk-based MAC protocol is carefully designed. By quantifying the WiFi throughput and packet delay in the coexisting system, we formulate the constraints of LAA-LTE transmission time to fairly maintain WiFi services. The conditions of known and unknown network size of incumbent WiFi system are each considered separately. Then, the feasible region of LAA-LTE transmission time is determined, and the LAA-LTE protocol is optimized for maximizing the LAA-LTE throughput or the overall throughput contributed by both LAA-LTE and WiFi system. The theoretical analysis is validated via simulation, which also illustrates important observations when LAA-LTE and WiFi systems coexist. This paper offers guidelines to design the LAA-LTE system, paving the way to a controllable, not only harmonious, coexistence of LAA-LTE and WiFi systems in the unlicensed spectrum.

The domain name system (DNS) is a core component of the Internet. It performs the vital task of mapping human readable names into machine readable data (such as IP addresses, which hosts handle e-mail, and so on). The content of the DNS reveals a lot about the technical operations of a domain. Thus, studying the state of large parts of the DNS over time reveals valuable information about the evolution of the Internet. We collect a unique long-term data set with daily DNS measure-ments for all the domains under the main top-level domains (TLDs) on the Internet (including .com , .net , and .org , comprising 50% of the global DNS name space). This paper discusses the challenges of performing such a large-scale active measurement. These challenges include scaling the daily measurement to collect data for the largest TLD ( .com , with 123M names) and ensuring that a measurement of this scale does not impose an unacceptable burden on the global DNS infrastructure. The paper discusses the design choices we have made to meet these challenges and documents the design of the measurement system we implemented based on these choices. Two case studies related to cloud e-mail services illustrate the value of measuring the DNS at this scale. The data this system collects is valuable to the network research community. Therefore, we end this paper by discussing how we make the data accessible to other researchers.

This paper introduces the mobile access coordinated wireless sensor network (MC-WSN)—a novel energy efficient scheme for time-sensitive applications. In conventional sensor networks with mobile access points (SENMA), the mobile access points (MAs) traverse the network to collect information directly from individual sensors. While simplifying the routing process, a major limitation with SENMA is that data transmission is limited by the physical speed of the MAs and their trajectory length, resulting in low throughput and large delay. In an effort to resolve this problem, we introduce the MC-WSN architecture, for which a major feature is that: through active network deployment and topology design, the number of hops from any sensor to the MA can be limited to a pre-specified number. In this paper, we investigate the optimal topology design that minimizes the average number of hops from sensor to MA, and provide the throughput analysis under both single-path and multipath routing cases. Moreover, putting MC-WSN in the bigger picture of network design and development, we provide a unified framework for wireless network modeling and characterization. Under this general framework, it can be seen that MC-WSN reflects the integration of structure-ensured reliability/efficiency and ad-hoc enabled flexibility.

With data center network traffic growing significantly, power-efficient optical and hybrid optical architectures are considered as an alternate to packet switching. Typically, hybrid optical architectures use fast optical switching elements to ensure any-to-any route reachability. In this paper, an optically groomed data center network (OGDCN) framework is proposed. The proposed framework supports any-to-any route reachability without using fast optical switching elements in the network. Different components can be combined to realize an OGDCN, as described in this paper. The framework is evaluated and compared to other architectures in terms of scalability and power consumption. A particular OGDCN realization is presented and is shown to be better than other architectures in terms of power consumption. The power consumption is lower by at least 47% than the next best existing architecture proposed in the literature.

This paper studies the energy efficiency of the cloud radio access network (C-RAN), specifically focusing on two fundamental and different downlink transmission strategies, namely the data-sharing strategy and the compression strategy. In the data-sharing strategy, the backhaul links connecting the central processor (CP) and the base-stations (BSs) are used to carry user messages -- each user's messages are sent to multiple BSs; the BSs locally form the beamforming vectors then cooperatively transmit the messages to the user. In the compression strategy, the user messages are precoded centrally at the CP, which forwards a compressed version of the analog beamformed signals to the BSs for cooperative transmission. This paper compares the energy efficiencies of the two strategies by formulating an optimization problem of minimizing the total network power consumption subject to user target rate constraints, where the total network power includes the BS transmission power, BS activation power, and load-dependent backhaul power. To tackle the discrete and nonconvex nature of the optimization problems, we utilize the techniques of reweighted $\ell_1$ minimization and successive convex approximation to devise provably convergent algorithms. Our main finding is that both the optimized data-sharing and compression strategies in C-RAN achieve much higher energy efficiency as compared to the non-optimized coordinated multi-point transmission, but their comparative effectiveness in energy saving depends on the user target rate. At low user target rate, data-sharing consumes less total power than compression, however, as the user target rate increases, the backhaul power consumption for data-sharing increases significantly leading to better energy efficiency of compression at the high user rate regime., Comment: 14 pages, 8 figures, accepted by JSAC Energy-Efficient Techniques for 5G Wireless Communication Systems special issue

With small cell networks becoming core parts of the fifth generation (5G) cellular networks, it is an important problem to evaluate the impact of user mobility on 5G small cell networks. However, the tendency and clustering habits in human activities have not been considered in traditional user mobility models. In this paper, human tendency and clustering behaviors are first considered to evaluate the user mobility performance for 5G small cell networks based on individual mobility model (IMM). As key contributions, user pause probability, user arrival and departure probabilities are derived in this paper for evaluat-ing the user mobility performance in a hotspot-type 5G small cell network. Furthermore, coverage probabilities of small cell and macro cell BSs are derived for all users in 5G small cell networks, respectively. Compared with the traditional random waypoint (RWP) model, IMM provides a different viewpoint to investigate the impact of human tendency and clustering behaviors on the performance of 5G small cell networks., Comment: 15 pages, 7 figures

In this paper, we present a novel licensed-shared access (LSA) spectrum-sharing scheme as an energy efficient way to increase the spectral utility of a network. We consider a two-tier network where a small cell network offers offloading services to a macro network to improve its quality of service. In return, the small cells are rewarded for their cooperation with a number of licenses to operate in the spectrum owned by the macro network. The short link distances and diversity offered by the small cell network to offload the macro user help enhance the total spectral and energy utilization of the network. For effective functioning of the scheme, it is important to determine the division between the fraction of small cells that provide offloading services and those which obtain the licenses. In this paper, we present a comprehensive mathematical model of this LSA-based offloading and evaluate the optimal division between the offloading and licensing small cells. Our analysis shows that such spectrum sharing can lead to commendable gains in the spectral utilization of the network while assuring the desired quality of service for both macro and small network. An intelligent determination of the fraction of offloading small cell network results in efficient energy use for offloading. We test our scheme within the network parameters of the city of Leeds, U.K. Our results indicate that the spectral utility of Leeds can be improved by more than $12\times$ , and the energy efficiency by $16\times$ through our proposed scheme.

This paper studies downlink communication in a heterogeneous cellular network where a set of geographically separated base stations (BSs) cooperates in transmitting data to a common receiver. If a decoding error occurs, data is cooperatively retransmitted by a possibly different set of BSs, such that the receiver can benefit from spatiotemporal BS cooperation. Specific cooperation techniques studied in this paper include joint transmission, base station silencing, and the Alamouti space-time code. Using tools from stochastic geometry, the coverage probability at the typical user is characterized as an integral function of the network parameters and the sets of cooperating BSs. The expressions derived reveal the existence of two qualitatively different operating regimes. In the high-coverage regime, the typical user is diversity-limited, so cooperation techniques exploiting spatiotemporal diversity are highly effective in increasing coverage. It is shown that retransmissions always yield time diversity, while channel state information at the transmitters is required to harvest spatial diversity via joint transmission. In the low-coverage regime, on the other hand, the typical user is interference-limited, so cooperation techniques such as joint transmission and base station silencing are effective in increasing coverage as they suppress part of the interference power.

The dominate spectrum sharing paradigm of today is interference avoidance, where a secondary network can use the spectrum only when such a use is not interfering with the primary network. However, with the advances of physical-layer technologies, the mindset of this paradigm is being challenged. This paper explores a new paradigm called “transparent coexistence” for spectrum sharing between primary and secondary nodes in a multihop network environment. Under this paradigm, the secondary network is allowed to use the same spectrum simultaneously with the primary network as long as their activities are “transparent” (or “invisible”) to the primary network. Such transparency is accomplished through a systematic interference cancelation (IC) by the secondary nodes without any impact on the primary network. Although such a paradigm has been studied in the information theory (IT) and communications (COMM) communities, it is not well understood in the wireless networking community, particularly for multihop networks. This paper offers an in-depth study of this paradigm in a multihop network environment and addresses issues such as scheduling (both in frequency channels and time slots) and IC (to/from primary network and within the secondary network). Through a rigorous modeling and formulation, problem formulation, solution development, and simulation results, we show that transparent coexistence paradigm offers significant improvement in terms of spectrum access and throughput performance as compared to the current prevailing interference avoidance paradigm.

Because of the asynchronization between primary and secondary wireless networks, the synchronization between primary users (PUs) and secondary users (SUs) can be hardly guaranteed in nontime-slotted cognitive radio networks (CRNs). In this paper, we propose a novel framework for multichannel nontime-slotted CRNs, where the PUs randomly access and leave the licensed channels. Since the PUs cannot distinguish between primary and secondary signals, the PUs may sense a busy channel when the PUs start to reactivate during the SUs' transmission, thus generating a collision or entering the backoff stage. To guarantee the high-throughput transmission of the PUs and increase the channel utilization of the SUs, in this paper, we propose the wireless full-duplex spectrum sensing (FD-SS) scheme for SUs in multichannel nontime-slotted CRNs. Using our developed FD-SS scheme, the SUs can timely sense the PUs' reactivation during the same time when the SUs are transmitting their signals. Then, based on our proposed wireless FD-SS scheme, we further develop and analyze the wireless full-duplex cognitive medium access control (FDC-MAC) protocol for multichannel nontime-slotted CRNs. We conduct extensive numerical analyses, showing that our developed FD-SS scheme and FDC-MAC protocol can efficiently guarantee the high-throughput transmission of the PUs and increase the channel utilization of the SUs without requiring the synchronization between the PUs and the SUs over the multichannel nontime-slotted CRNs.

In this paper, we consider the random access of nodes having energy harvesting capability and a battery to store the harvested energy. Each node attempts to transmit the head-of-line packet in the queue if its battery is nonempty. The packet and energy arrivals into the queue and the battery are all modeled as a discrete-time stochastic process. The main contribution of this paper is the exact characterization of the stability region of the packet queues given the energy harvesting rates when a pair of nodes are randomly accessing a common channel having multipacket reception (MPR) capability. The channel with MPR capability is a generalized form of the wireless channel modeling which allows probabilistic receptions of the simultaneously transmitted packets. The results obtained in this paper are fairly general as the cases with unlimited energy for transmissions both with the collision channel and the channel with MPR capability can be derived from ours as special cases. Furthermore, we study the impact of the finiteness of the batteries on the achievable stability region., Comment: The material in this paper was presented in part at the IEEE International Symposium on Information Theory, Saint Petersburg, Russia, Aug. 2011

A robust Ergodic Resource Allocation (ERA) scheme is proposed in this paper in the framework of an orthogonal frequency division multiple access (OFDMA) based underlay heterogeneous network in which the allocations are made so as to maximize the average network sum-rate while guaranteeing the macro network interference requirements with any desired high probability. In previously proposed ERA schemes, both in conventional and heterogeneous networks, the optimal solution is obtained assuming that average of constraints are satisfied. In a heterogeneous network, this is translated into the fact that instantaneous level of interference on macro users can not be guaranteed, i.e., there is an uncontrolled probability of collision which is not acceptable by macro network. In this paper, we reformulate the ERA problem by replacing the average based constraints, in our case, femto total power constraint and macro interference threshold constraint, with their probabilistic counterparts so that both constraints are satisfied instantaneously with any desired high probability. We consider both cases of continuous and quantized channel state information. The proposed problems are then solved based on three methods, namely, iterative, analytical, and hybrid approaches. The optimality of the proposed methods is also assessed and the iterative approach is shown to have a performance quite close to that of the optimal solution. Simulation results confirm the effectiveness of the proposed scheme to provide a robust instantaneous imposed interference on macro network and a robust femto total transmit power. We also investigate the convergence properties of the proposed iterative approach.

The next-generation advanced metering infrastructure, with the aid of two-way smart meters, is expected to support advanced functions such as remote reading and control and demand response. In this paper, we thus focus on the design of a smart metering network (SMN) for a future scenario where data from residences/customer premises are dominated by electric vehicle charging traffic. Therefore, the well-suited multiple access control (MAC) protocol design for such event-driven data is an emerging research area. However, because the number of smart meters (communication nodes) involved in such a single SMN is much larger than those in today's local area networks, the traditional random access MAC protocol is unlikely to perform well. In order to solve this problem, we propose two grouping-based MAC protocols, namely, TDMA-DCF and group leader DCF-TDMA schemes, in this paper. These two schemes are directed at 802.11-type networks operating at frequencies below 1 GHz, which has been adopted by a new IEEE 802.11ah standardization task group. We also conduct the comprehensive throughput and delay analysis on these schemes for unsaturated traffic conditions and hidden node events. The numerical results show that these two grouping-based MAC protocols significantly outperform the traditional random access protocol DCF in a densely populated network with large coverage such as SMN.

The material in this paper was presented in part at the 4th IEEE Workshop on Cooperative and Cognitive Mobile Networks (CoCoNet), collocated with IEEE ICC 2012. This paper investigates cooperation for secrecy in cognitive radio networks. In particular, we consider a four-node cognitive scenario where the secondary receiver is treated as a potential eavesdropper with respect to the primary transmission. The cognitive transmitter can help the primary transmission, and it should also ensure that the primary message is not leaked to the secondary user. We consider two cognitive scenarios depending on whether the secondary transmitter knows the primary message or not. In the first case, the secondary transmitter is unaware of the primary transmitter's message and acts as a helping interferer to enhance the secrecy of the primary transmission, whereas in the second case, relaying of the primary message is also within its capabilities. First, we find achievable rate regions for these two scenarios in the case of AWGN channels. We then investigate three different optimization problems: the maximization of the primary rate, the maximization of the secondary rate and the minimization of the secondary transmit power. For these optimization problems, we find closed-form expressions in important special cases. Furthermore, we analyze the cooperation between the primary and secondary transmitters from a game-theoretic perspective. We model their interaction as a Stackelberg game, for which we define and find the Stackelberg equilibrium. Finally, we use numerical examples to illustrate the rate regions, the three optimizations, and the impact of the Stackelberg game on the achievable rates and on the transmission strategies of the secondary transmitter. Refereed/Peer-reviewed

In the orthogonal frequency division multiple access (OFDMA) system, one of the efficient and low complex methods to allocate radio resources among multiple users is chunk-based resource allocation, which groups a number of adjacent subcarriers into a chunk and allocates resources chunk by chunk. In this paper, performance analysis of chunk-based resource allocation is studied in the multi-cell OFDMA environment. Fractional frequency reuse (FFR) is considered in the cellular OFDMA. Basically, FFR divides each cell into central and edge areas where two different values of the frequency reuse factor are assumed. This paper analytically evaluates how spectral efficiency performance is affected by system parameters, including radius ratio of the central area to the whole cell, transmit signal to noise ratio (SNR), number of users, number of subcarriers per chunk, and coherence bandwidth. The numerical results show that there exists an optimal radius ratio to achieve the highest spectral efficiency in the proposed research. The optimal radius ratio is about 0.7, which is almost irrespective of the SNR, number of users, and number of subcarriers per chunk. In other words, the sizes of the central area and the edge area of the whole cell are almost equal when achieving the optimal performance.

This paper is concerned with the decentralized power allocation problem in random access systems. We propose a scheme that is especially suitable for systems requiring high throughput but with difficulty in establishing centralized control, such as cognitive radio environments. Specifically, we assume successive interference cancellation (SIC) at the receiver for multi-packet reception (MPR). We consider a decentralized random power transmission strategy where each user selects its transmitted power level randomly according to a power distribution conditioned on its own channel state. Our focus is on the design of this distribution such that the system packet throughput is maximized under rate and power constraints. We start from a two-user system. A main finding of this paper is that the supports of the optimal power distributions are of discrete nature. This finding greatly simplifies the distribution optimization problem. We also discuss a sub-optimal solution to systems with more than two users. Numerical results demonstrate that the proposed scheme can achieve noticeable performance improvement compared with conventional single-user detection (SUD) based ones and offer a flexible tradeoff between the system throughput and power consumption.

This paper studies an uplink multicell joint processing model in which the base-stations are connected to a centralized processing server via rate-limited digital backhaul links. Unlike previous studies where the centralized processor jointly decodes all the source messages from all base-stations, this paper proposes a suboptimal achievability scheme in which the Wyner-Ziv compress-and-forward relaying technique is employed on a per-base-station basis, but successive interference cancellation (SIC) is used at the central processor to mitigate multicell interference. This results in an achievable rate region that is easily computable, in contrast to the joint processing schemes in which the rate regions can only be characterized by exponential number of rate constraints. Under the per-base-station SIC framework, this paper further studies the impact of the limited-capacity backhaul links on the achievable rates and establishes that in order to achieve to within constant number of bits to the maximal SIC rate with infinite-capacity backhaul, the backhaul capacity must scale logarithmically with the signal-to-interference-and-noise ratio (SINR) at each base-station. Finally, this paper studies the optimal backhaul rate allocation problem for an uplink multicell joint processing model with a total backhaul capacity constraint. The analysis reveals that the optimal strategy that maximizes the overall sum rate should also scale with the log of the SINR at each base-station., JSAC Oct 2013, special issue on VMIMO

Extensive studies have shown that the peer-to-peer (P2P) traffic has already become the dominant traffic in the current Internet. The current P2P streaming user base is still undergoing stunning growth in China although its user scale already reached 158 million in 2010, 68% of Chinese web users. Hence, a comprehensive understanding of the P2P streaming network traffic characterization is essential to Internet Service Providers (ISPs) in terms of network planning and resource allocation. In this paper, based on the massive data collected with a passive network monitoring equipment placed in the Internet backbone, we provide an in-depth view of the current P2P streaming traffic in the current Internet of China. In particular, we statistically study the P2P streaming traffic in both wired (ADSL in this paper) and wireless (CDMA) networks, and characterize the traffic from both flow-level and packet-level aspects. Our study uncovers the significant impact of the P2P streaming traffic on the underlying network due to its unique characteristics and the bandwidth intensive nature of the corresponding applications. In addition, the result reveals the significant difference between the characterizations of the P2P streaming traffic in wired and wireless networks due to their respective intrinsic environmental characteristics.

This paper addresses the problem of identifying the top-k information hubs in a social network. Identifying top-k information hubs is crucial for many applications such as advertising in social networks where advertisers are interested in identifying hubs to whom free samples can be given. Existing solutions are centralized and require time stamped information about pair-wise user interactions and can only be used by social network owners as only they have access to such data. Existing distributed algorithms suffer from poor accuracy. In this paper, we propose a new algorithm to identify information hubs that preserves user privacy. Our method can identify hubs without requiring a central entity to access the complete friendship graph. We achieve this by fully distributing the computation using the Kempe-McSherry algorithm, while addressing user privacy concerns. We evaluate the effectiveness of our proposed technique using three real-world data set; The first two are Facebook data sets containing about 6 million users and more than 40 million friendship links. The third data set is from Twitter and comprises of a little over 2 million users. The results of our analysis show that our algorithm is up to 50% more accurate than existing algorithms. Results also show that the proposed algorithm can estimate the rank of the top-k information hubs users more accurately than existing approaches.

Characterization of communication links in Aerial Wireless Sensor Networks (AWSN) is of paramount importance for achieving acceptable network performance. Protocols based on an arbitrary link performance threshold may exhibit inconsistent behavior due to link behavior not considered during the design stage. It is thus necessary to account for factors that affect the link performance in real deployments. This paper details observations from an extensive set of experiments designed to characterize the behavior of communication links in AWSN. We employ the widely used TelosB sensor platform for these experiments. The experimental results highlight the fact that apart from the usual outdoor environmental factors affecting the link performance, two major contributors to the link degradation in AWSN are the antenna orientation, and the multi-path fading effect due to ground reflections. Based on these observations, we propose a Link Aware Protocol for AWSN (LAAWN) that takes into account the effect of these potential sources of performance degradation. This paper details the design and performance evaluation of our proposed LAAWN protocol. We evaluated the LAAWN protocol in two real-world use cases namely delay-tolerant and real-time AWSN. The simulation results show that on average, LAAWN improves the overall network performance by reducing the percentage of dropped packets from about 34% to less than 4% for an AWSN that requires real-time data transfer.

This paper presents closed-form capacity expressions for interfere-limited relay channels. Existing theoretical analysis has primarily focused on Gaussian relay channels, and the analysis of interference-limited relay deployment has been confined to simulation based approaches. The novel contribution of this paper is to consolidate on these approaches by proposing a theoretical analysis that includes the effects of interference and capacity saturation of realistic transmission schemes. The performance and optimization results are reinforced by matching simulation results. The benefit of this approach is that given a small set of network parameters, the researcher can use the closed-form expressions to determine the capacity of the network, as well as the deployment parameters that maximize capacity without committing to protracted system simulation studies. The deployment parameters considered in this paper include the optimal location and number of relays, and resource sharing between relay and base-stations. The paper shows that the optimal deployment parameters are pre-dominantly a function of the saturation capacity, pathloss exponent and transmit powers. Furthermore, to demonstrate the wider applicability of the theoretical framework, the analysis is extended to a multi-room indoor building. The capacity improvements demonstrated in this paper show that deployment optimization can improve capacity by up to 60% for outdoor and 38% for indoor users. The proposed closed-form expressions on interference-limited relay capacity are useful as a framework to examine how key propagation and network parameters affect relay performance and can yield insight into future research directions.

This paper addresses the challenge of how to reduce the energy consumption of a multi-cell network under a dynamic traffic load. The body of investigation first shows that the energy reduction upper-bound for transmission improving techniques is hardware-limited, and the bound for infrastructure reduction is capacity-limited. The paper proposes a novel cell expansion technique, where the coverage area of cells can expand and contract based on the traffic load. This is accomplished by switching off low load cell-sites and compensating for the coverage loss by expanding the neighboring cells through antenna beam tilting. The multi-cell coordination is resolved by using either a centralized controller or a distributed self-organizing-network (SON) algorithm. The analysis demonstrates that the proposed distributed algorithm is able to exploit flexibility and performance uncertainty through reinforced learning and improves on the centralized solution. The combined energy saving benefit of the proposed techniques is up to 50% compared to a reference deployment and 44% compared with alternative state-of-the-art dynamic base-station techniques.

Elastic optical networking (EON) has emerged in recent years as a promising solution for implementing flexible bandwidth channels (flexpaths) that efficiently match the allocated bandwidth with the traffic demand using agile granularities of spectrum allocation. However, the additional flexibility in such networks raises challenges in terms of efficient control and management of spectrum resources. Among them, three important issues are (1) mitigation of spectral fragmentation, (2) implementation of impairment awareness and enhancement of robustness against impairments for potentially large-bandwidth flexpaths, and (3) design of an efficient restoration scheme to combat network failures. This paper presents an adaptive spectrum control and management scheme, which includes: dynamic on-demand spectral defragmentation, adaptive combinational quality of transmission (QoT) restoration (ACQR) and supervisory channel-assisted active restoration, to account for the three issues above. We present scalable networking algorithms and experimental demonstrations that address these issues in an EON testbed. Simulation results show that the defragmentation technique is capable of reducing the provisioning blocking probability by half with only one defragmentation module on each link. Then, we also show that the ACQR can efficiently restore many degraded flexpaths on the same impaired link while reducing the restoration blocking probability by a factor of 10 compared with the conventional rerouting method. At last, we show via simulation the advantages of using supervisory channels to determine restoration path quality and selection in EON restorations. This paper also presents experimental demonstrations to corroborate the effectiveness and feasibility of implementing these capabilities in next generation optical networks.

An abstraction of the physical-layer coding using bit pipes that are coupled through data-rates is insufficient to capture notions such as node cooperation in cooperative relay networks. Consequently, network-stability analyses based on such abstractions are valid for non-cooperative schemes alone and meaningless for cooperative schemes. Motivated from this, this paper develops a framework that brings the information-theoretic coding scheme together with network-stability analysis. This framework does not constrain the system to any particular achievable scheme, i.e., the relays can use any cooperative coding strategy of its choice such as amplify/compress/quantize or any alter-and-forward scheme. The paper focuses on the scenario when coherence duration is of the same order of the packet/codeword duration, the channel distribution is unknown and the fading state is only known causally. The main contributions of this paper are two-fold: first, it develops a low-complexity queue-architecture to enable stable operation of cooperative relay networks, and, second, it establishes the throughput optimality of a simple network algorithm that utilizes this queue-architecture.

The activity around the standardization of an IEEE 802.11 mesh protocol has gained momentum in recent years. The mesh architecture presents a huge potential for multiple device-to-device communication, which will likely be realized through multi-channel access techniques. Prior studies on multi-channel access focus on routing and media access control (MAC) layers and are limited primarily to analysis and simulation. In this paper, we present the application of a novel approach called distributed information sharing (DISH) to provide a simple multi-channel access solution for 802.11 mesh networks. We present a cooperative multi-channel access extension of the 802.11 MAC protocol by incorporating DISH into the IEEE 802.11 DCF design and implement the protocol using commodity 802.11 hardware and open source Linux drivers. The paper also presents protocol design considerations, implementation challenges and experimental results from a mesh testbed. The study clearly demonstrates the performance superiority of the technique under heavy traffic conditions and confirms that cooperative multi-channel access is a promising technology for boosting the performance of 802.11 mesh networks.

This paper proposes group decoding and analyzes the associated rate allocation schemes for the relay interference channel where multiple relays assist the transmissions from the sources to destinations. All the relays and destinations employ an advanced decoding strategy called constrained group decoding, where the desired messages are decoded jointly with some interferers' messages when doing so is beneficial. This paper considers two types of relay systems, the hopping relay system with no direct source-destination links, and the inband relay system with direct source-destination links. For each relay type, the objective is to design the relay assignment and the group decoding strategies at the relays and destinations, in order to maximize the minimum information rate among all source-destination pairs. For hopping relays with pre-specified relay assignments, we provide the optimal distributed algorithm for solving the above max-min rate allocation problem. Moreover, for hopping relays with dynamic relay assignments, and for inband relays, the problem becomes intractable and we offer heuristic schemes that perform close to the optimum solutions. Numerical results demonstrate the significant performance improvement provided by the proposed group decoder over the traditional systems that employ the linear minimum mean-square error (MMSE) decoders at both the relays and the destinations, where all interference is treated as noise, as well as the effectiveness of the proposed dynamic relay assignment strategies.

Nowadays, multimedia applications and specifically streaming systems over wireless networks use the TCP transport protocol. Indeed, TCP can deal with practical issues such as firewalls and also deploys built-in retransmissions and congestion control mechanisms. We propose in this paper a Quality-centric Mean Opinion Score (MOS) based congestion control that determines an optimal congestion window updating policy for multimedia transmission. Unlike the standard congestion control algorithms, our approach defines a new Additive Increase Multiplicative Decrease (AIMD) algorithm given the multimedia application and the transmission characteristics. In order to get the optimal congestion policy in practice, the sender requires complete statistical knowledge of both multimedia traffic and the network environment, which may not be available in wireless systems. Hence, we propose in this paper, a Partially Observable Markov Decision Process (POMDP) framework in order to determine an optimal congestion control policy which maximizes the long term expected Quality of Experience (QoE) of the receiver. Moreover, the computation of an optimal policy is usually time/process consuming and as wireless devices are capacity-limited, we consider optimal solutions based on temporal difference (TD-λ) online learning algorithms. Finally, we do some practical experiments of our algorithm on a Microsoft Lync testbed with unidirectional and bidirectional communications over a wireless network. We observe that for both scenarios, our algorithm improves significantly the QoE compared to standard AIMD congestion control mechanism.