Interference creates a fundamental barrier in attempting to improve throughput in wireless networks, especially when multiple concurrent transmissions share the wireless medium. In recent years, significant progress has been made on characterizing the capacity limits of wireless networks under the premise of global and instantaneous channel state information at transmitter (CSIT). In practice, however, the acquisition of such instantaneous and global CSIT as a means toward cooperation is highly challenging due to the distributed nature of transmitters and dynamic wireless propagation environments. In many limited CSIT scenarios, the promising gains from interference management strategies using instantaneous and global CSIT disappear, often providing the same result as cases where there is no CSIT. Is it possible to obtain substantial performance gains with limited CSIT in wireless networks, given previous evidence that there is marginal or no gain over the case with no CSIT? To shed light on the answer to this question, in this dissertation, I present several achievable sum of degrees of freedom (sum-DoF) characterizations of wireless networks. The sum-DoF is a coarse sum-capacity approximation of the networks, deemphasizing noise effects. These characterizations rely on a set of proposed and existing interference management strategies that exploit limited CSIT. I begin with the classical multi-user multiple-input-single-output (MISO) broadcast channel with delayed CSIT and show how CSI feedback delays change sum-capacity scaling law by proposing an innovative interference alignment technique called space-time interference alignment. Next, I consider interference networks with distributed and delayed CSIT and show how to optimally use distributed and moderately-delayed CSIT to yield the same sum-DoF as instantaneous and global CSIT using the idea of distributed space-time interference alignment. I also consider a two-hop layered multiple-input-multiple-output (MIMO) interference channel, where I show that two cascaded interfering links can be decomposed into two independent parallel relay channels without using CSIT at source nodes through the proposed interference-free relaying technique. Then I go beyond one-way and layered to multi-way and fully-connected wireless networks where I characterize the achievable sum-DoF of networks where no CSIT is available at source nodes using the proposed space-time physical-layer network coding. Lastly, I characterize analytical expressions for the sum spectral efficiency in a large-scale single-input-multiple- output (SIMO) interference network where the spatial locations of nodes are modeled by means of stochastic geometry. I derive analytical expressions for the ergodic sum spectral efficiency and the scaling laws as functions of relevant system parameters depending on different channel knowledge assumptions at receivers. / text

In this thesis, advanced interference management techniques are designed and evaluated for large-scale wireless networks with realistic assumptions, such as signal propagation loss, random node distribution and non-instantaneous channel state information at the transmitter (CSIT). In the first part of the thesis, the Maddah-Ali and Tse (MAT) scheme for the 2-user and 2-antenna base station (BS) broadcast channel (BC) is generalised and optimised using the probabilistic-constrained optimisation approach. With consideration of the unknown channel entries, the proposed optimisation approach guarantees a high probability that the interference leakage power is below a certain threshold in the presence of minimum interference leakage receivers. The desired signal detectability is maximised at the same time and the closed-form solution for the receiving matrices is provided. Afterwards, the proposed optimisation approach is extended to the 3-user BC with 2-antenna BS. Simulation results show substantial sum rate gain over the MAT scheme, especially with a large spatial correlation at the receiver side. In the second part, the MAT scheme is extended to the time-correlated channels in three scenarios, in which degrees of freedom (DoF) regions as well as achievability schemes are studied: 1) 2-user interference channel (IC) using imperfect current and imperfect delayed CSIT; 2) K-user BC with K-antenna BS using imperfect current and perfect delayed CSIT; 3) 3-user BC with 2-antenna BS using imperfect current and perfect delayed CSIT. Notably, the consistency of the proposed DoF regions with the MAT scheme and the ZF beamforming schemes using perfect current CSIT consents to the optimality of the proposed achievability schemes. In the third part, the performance of the ZF receiver is evaluated in Poisson distributed wireless networks. Simple static networks as well as dynamic networks are studied. For the static network, transmission capacity is derived whereby the receiver can eliminate interference from nearby transmitters. It is shown that more spatial receive degrees of freedom (SRDoF) should be allocated to decode the desired symbol in the presence of low transmitter intensity. For the dynamic network, in which the data traffic is modelled by queueing theory, interference alignment (IA) beamforming is considered and implemented sequentially. Interestingly, transmitting one data stream achieves the highest area spectrum efficiency. Finally, a distance-dependent IA beamforming scheme is designed for a generic 2-tier heterogeneous wireless network. Second-tier transmitters partially align their interferences to the dominant cross-tier interference overheard by the receivers in the same cluster. Essentially, the proposed IA scheme compromises between enhancing the signal-to-interference ratio and increasing the multiplexing gain. It is shown that acquiring accurate distance knowledge brings insignificant throughput gain compared to statistical distance knowledge. Simulation results validate the derived expressions of success probabilities as well as throughput, and show that the distance-dependent IA scheme significantly outperforms the traditional IA scheme in the presence of path-loss effect.

Today and future wireless networks are facing one of their greatest limiting factors:interference. This is due to the unprecedented increase in the number of connecteddevices. Therefore, in order to meet the ever increasing demand for data rate andquality of services, more advanced techniques than what we have today are requiredto deal with interference. This thesis takes a step towards interference managementin multiuser wireless systems by means of relaying and cooperation. We study fourfundamental building blocks in network information theory, propose new codingschemes, and derive limits on the capacity regions. The first problem we consider is the one-sided interference channel with bidirectional and rate-limited receiver cooperation. We propose a coding scheme that tailors two versions of superposition coding with classical relaying protocols. Theproposed scheme unifies and recovers previous results for the unidirectional coop-eration, yet in simpler forms. Analytical and numerical results confirm the benefitsof cooperation and illuminate the ideas behind the coding strategy. The second problem generalizes the first one by allowing the existence of bothcrossover links in the channel. We propose a coding scheme for this channel byextending noisy network coding to encompass rate-splitting at the encoders. Theachievable rate region is shown to be the same as a region achieved by explicitbinning. As a corollary, we prove that noisy network coding achieves the capacityregion of the Gaussian channel within 1 bit, under strong interference. Our resultis among the first to show constant-gap optimality of noisy network coding for amultiple-unicast problem, and to demonstrate equivalence in terms of achievablerates of two different coding approaches for a noisy interference network. We follow up by introducing a dedicated relay into the interference channelwhich simultaneously helps both receivers. For this third problem, the interferencechannel with a relay, we propose new coding schemes based on layered codes for long- and short-message quantize-forward techniques. The short-message schemesshow improvements in the achievable rates compared to other known coding tech-niques, especially when the channel is asymmetric, while relaxing the excessive delayissue of the long-message scheme. The analysis also reveals the trade-off betweenachievable rates, encoding and decoding delays, and complexity. In the fourth problem, we propose a new model for cooperative communication,the interfering relay channels, which consists of two neighboring relay channelsinducing interference to each other. Each relay, by utilizing a finite-capacity andnoise-free link to its own receiver, helps the receiver decode the desired message.We characterize the exact and approximate capacity region and sum-capacity forvarious classes of channels. The established results generalize and unify severalknown results for the relay and interference channels.The methods and results shown in this thesis aim at providing insight intopotential techniques for cooperative interference management in real-world systems. / <p>QC 20131001</p>

<div> Interference management is necessary to meet the growth in demand for wireless data services. The problem was studied in previous work by assuming a fixed channel connectivity model, while network topologies tend to change frequently in practice. </div><div><br></div><div>The associations between cell edge mobile terminals and base stations in a wireless interference network that is backed by cooperative communication schemes is investigated and association decisions are identified that are information-theoretically optimal when taking the uplink-downlink average. Then, linear wireless networks are evaluated from a statistical point of view, where the associations between base stations and mobile terminals are fixed and channel fluctuations exist due to shadow fading. Moreover, the considered fading model is formed by having links in the wireless network, each subject independently to erasure with a known probability. </div><div><br></div><div>Throughout the information theoretic analysis, it is assumed that the network topology is known to the cooperating transmitting nodes. This assumption may not hold in practical wireless networks, particularly Ad-Hoc ones, where decentralized mobile nodes form a temporary network. Further, communication in many next generation networks, including cellular, is envisioned to take place over different wireless technologies, similar to the co-existence of Bluetooth, ZigBee, and WiFi in the 2.4 GHz ISM-Band. The competition of these wireless technologies for scarce spectrum resources confines their coexistence. It is hence elementary for collaborative interference management strategies to identify the channel type and index of a wireless signal, that is received, to promote intelligent use of available frequency bands. It is shown that deep learning based approaches can be used to identify interference between the wireless technologies of the 2.4 GHz ISM-Band effectively, which is compulsory for identifying the channel topology. The value of using deep neural network architectures such as CNN, CLDNN, LSTM, ResNet and DenseNet for this problem of Wireless Channel Identification is investigated. Here, the major focus is on minimizing the time, that takes for training, and keeping a high classification accuracy of the different network architectures through band and training SNR selection, Principal Component Analysis (PCA) and different sub-Nyquist sampling techniques. </div><div>Finally, a number theoretic approach for fast discovery of the network topology is proposed. More precisely, partial results on the simulation of the message passing model are utilized to present a model for discovering the network topology. Specifically, the minimum number of communication rounds needed to discover the network topology is examined. Here, a single-hop network is considered that is restricted to interference-avoidance, i.e., a message is successfully delivered if and only if the transmitting node is the only active transmitter connected to its receiving node. Then, the interference avoidance restriction is relaxed by assuming that receivers can eliminate interference emanating from already discovered transmitters. Finally, it is explored how the network size and the number of interfering transmitters per user adjust the sum of observations.</div><div><br></div>

ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / This paper presents a method for the management of mixed networks as envisioned in future iNET applications and develops a scheme for global optimal performance for features that include signal to Noise Ratio (SNR), Quality of service (QoS), and Interference. This scheme demonstrates potential for significant enhancement of performance for dense traffic environments envisioned in future telemetry applications. Previous research conducted at Morgan State University has proposed a cellular and Ad hoc mixed network for optimum capacity and coverage using two distance measures: QoS and SNR. This paper adds another performance improvement technique, interference, as a third distance measure using an analytical approach and using extensive simulation with MATLAB. This paper also addresses solutions where performance parameters are correlated and uncorrelated. The simulations show the optimization of mixed network nodes using distance, traffic and interference measures all at one time. This has great potential in mobile communication and iNET.

This dissertation investigates how to optimize flow-level performance in interference dominated wireless networks serving dynamic traffic loads. The schemes presented in this dissertation adapt to long-term (hours) spatial load variations, and the main metrics of interest are the file transfer delay or average flow throughput and the mean power expended by the transmitters. The first part presents a system level approach to interference management in an infrastructure based wireless network with full frequency reuse. The key idea is to use loose base station coordination that is tailored to the spatial load distribution and the propagation environment to exploit the diversity in a user population's sensitivity to interference. System architecture and abstractions to enable such coordination are developed for both the downlink and the uplink cases, which present differing interference characteristics. The basis for the approach is clustering and aggregation of traffic loads into classes of users with similar interference sensitivities that enable coarse grained information exchange among base stations with greatly reduced communication overheads. The dissertation explores ways to model and optimize the system under dynamic traffic loads where users come and go resulting in interference induced performance coupling across base stations. Based on extensive system-level simulations, I demonstrate load-dependent reductions in file transfer delay ranging from 20-80% as compared to a simple baseline not unlike systems used in the field today, while simultaneously providing more uniform coverage. Average savings in user power consumption of up to 75% are achieved. Performance results under heterogeneous spatial loads illustrate the importance of being traffic and environment aware. The second part studies the impact of policies to associate users with base stations/access points on flow-level performance in interference limited wireless networks. Most research in this area has used static interference models (i.e., neighboring base stations are always active) and resorted to intuitive objectives such as load balancing. In this dissertation, it is shown that this can be counter productive, and that asymmetries in load can lead to significantly better performance in the presence of dynamic interference which couples the transmission rates experienced by users at various base stations. A methodology that can be used to optimize the performance of a class of coupled systems is proposed, and applied to study the user association problem. It is demonstrated that by properly inducing load asymmetries, substantial performance gains can be achieved relative to a load balancing policy (e.g., 15 times reduction in mean delay). A novel measurement based, interference-aware association policy is presented that infers the degree of interference induced coupling and adapts to it. Systematic simulations establish that both the optimized static and interference-sensitive, adaptive association policies substantially outperform various proposed dynamic policies and that these results are robust to changes in file size distributions, channel parameters, and spatial load distributions. / text

In this thesis, we study a three-node full-duplex network, where the infrastructure node has simultaneous up- and downlink communication in the same frequency band with two half-duplex nodes. In addition to self-interference at the full-duplex infrastructure node, the three-node network has to contend with the inter-node interference between the two half-duplex nodes. The two forms of interferences differ in one important aspect that the self-interference is known at the interfered receiver. Therefore, we propose to leverage a wireless side-channel to manage the inter-node interference. We characterize the impact of inter-node interference on the network achievable rate region with and without a side-channel between the nodes. We present four distributed full-duplex inter-node interference cancellation schemes, which leverage the device-to-device wireless side-channel for improved interference cancellation. Of the four, bin-and-cancel is asymptotically optimal in high signal-to-noise ratio limit which uses Han-Kobayashi common-private message splitting and achieves within 1 bits/s/Hz of the capacity region for all values of channel parameters. The other three schemes are simpler compared to bin-and-cancel but achieve the near-optimal performance only in certain regimes of channel values. Asymptotic multiplexing gains of all proposed schemes are derived to show analytically that leveraging the side channel can be highly beneficial in increasing the multiplexing gain of the system exactly in those regimes where inter-node interference has the highest impact.

We present a vision for 4G cellular networks based on the concept of autonomous infrastructure deployment. Cellular base stations, or femtocell access points, are deployed by network users without being constrained by the conventional cell planning process from the network operator. Autonomous deployment allows the network to grow in an organic manner which requires new methods for spectrum management. We study a framework for autonomous network optimization based on the method of cognitive interference management. In our model, a number of femtocells are co-channel deployed in an underlay macrocellular network. Instead of fully reusing 100% of the macrocellular resource, partial reuse is cognitively determined in femtocells based on their individual network environment. According to an interference signature perceived from the environment, a femtocell autonomously determines the appropriate channel allocation and minimizes the network interference. Upon the cognitive acquisition of the random infrastructure topology, base station pilot power is autonomously configured in order to maximize the cellular coverage. A series of network self-configuration procedures are discussed for automatic cell size adaptation and resource management. Our results show that the new approaches based on cognitive radio configuration facilitate the network optimization in terms of interference management, mobile handoff, pilot power control and network resource allocation. The proposed framework offers a 4G vision for spectrum management in an autonomous self-managed cellular architecture.

We present a vision for 4G cellular networks based on the concept of autonomous infrastructure deployment. Cellular base stations, or femtocell access points, are deployed by network users without being constrained by the conventional cell planning process from the network operator. Autonomous deployment allows the network to grow in an organic manner which requires new methods for spectrum management. We study a framework for autonomous network optimization based on the method of cognitive interference management. In our model, a number of femtocells are co-channel deployed in an underlay macrocellular network. Instead of fully reusing 100% of the macrocellular resource, partial reuse is cognitively determined in femtocells based on their individual network environment. According to an interference signature perceived from the environment, a femtocell autonomously determines the appropriate channel allocation and minimizes the network interference. Upon the cognitive acquisition of the random infrastructure topology, base station pilot power is autonomously configured in order to maximize the cellular coverage. A series of network self-configuration procedures are discussed for automatic cell size adaptation and resource management. Our results show that the new approaches based on cognitive radio configuration facilitate the network optimization in terms of interference management, mobile handoff, pilot power control and network resource allocation. The proposed framework offers a 4G vision for spectrum management in an autonomous self-managed cellular architecture.

Two-tier macrocell-femtocell network is considered an efficient solution to enhance area spectral-efficiency, improve cell coverage and provide better quality-of-service (QoS) to mobile users. However, interference and mobility management are considered to be the major issues for successful deployment of macrocell-femtocell network. In this thesis, a unified framework is developed for interference management, resource allocation, and call admission control (CAC) for two-tier macrocell-femtocell network. Fractional frequency reuse (FFR) is considered to provide both link-level and call-level QoS measures for mobile users. In this framework, joint resource allocation and interference coordination problem is formulated as an optimization problem to obtain design parameters for sectored FFR. The CAC problem is formulated as Semi-Markov Decision Process and Value Iteration Algorithm is used to obtain optimal admission control policy. Performance of this framework is evaluated through simulations. The performance evaluation results show that the proposed framework outperforms traditional non-optimized FFR scheme in two-tier network.