Browsing by Subject "Interference management"
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Item Interference alignment from theory to practice(2013-05) El Ayach, Omar; Heath, Robert W., Ph. D.Wireless systems in which multiple users simultaneously access the propagation medium suffer from co-channel interference. Untreated interference limits the total amount of data that can be communicated reliably across the wireless links. If interfering users allocate a portion of the system's resources for information exchange and coordination, the effect of interference can be mitigated. Interference alignment (IA) is an example of a cooperative signaling strategy that alleviates the problem of co-channel interference and promises large gains in spectral efficiency. To enable alignment in practical wireless systems, channel state information (CSI) must be shared both efficiently and accurately. In this dissertation, I develop low-overhead CSI feedback strategies that help networks realize the information-theoretic performance of IA and facilitate its adoption in practical systems. The developed strategies leverage the concepts of analog, digital, and differential feedback to provide IA networks with significantly more accurate and affordable CSI when compared to existing solutions. In my first contribution, I develop an analog feedback strategy to enable IA in multiple antenna systems; multiple antennas are one of IA's key enabling technologies and perhaps the most promising IA use case. In my second contribution, I leverage temporal correlation to improve CSI quantization in limited feedback single-antenna systems. The Grassmannian differential strategy developed provides several orders of magnitude in CSI compression and ensures almost-perfect IA performance in various fading scenarios. In my final contribution, I complete my practical treatment of IA by revisiting its performance when CSI acquisition overhead is explicitly accounted for. This last contribution settles the viability of IA, from a CSI acquisition perspective, and demonstrates the utility of the proposed feedback strategies in transitioning interference alignment from theory to practice.Item Interference management with limited channel state information in wireless networks(2014-12) Lee, Namyoon; Heath, Robert W., Ph. D.; Baccelli, F. (François), 1954-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.Item Limited feedback MIMO for interference limited networks(2012-12) Akoum, Salam Walid; Heath, Robert W., Ph. D.; Andrews, Jeffrey G.; Sanghavi, Sujay; Debbah, Merouane; Vikalo, Haris; Kountouris, MariosManaging interference is the main technical challenge in wireless networks. Multiple input multiple output (MIMO) methods are key components to overcome the interference bottleneck and deliver higher data rates. The most efficient MIMO techniques require channel state information (CSI). In practice, this information is inaccurate due to errors in CSI acquisition, as well as mobility and delay. CSI inaccuracy reduces the performance gains provided by MIMO. When compounded with uncoordinated intercell interference, the degradation in MIMO performance is accentuated. This dissertation investigates the impact of CSI inaccuracy on the performance of increasingly complex interference limited networks, starting with a single interferer scenario, continuing to a heterogeneous network with a femtocell overlay, and finishing with a clustered multicell coordination model for randomly deployed transmitting nodes. First, this dissertation analyzes limited feedback beamforming and precoded spatial multiplexing over temporally correlated channels. Assuming uncoordinated interference from one dominant interferer, using Markov chain convergence theory, the gain in the average successful throughput at the mobile user is shown to decrease exponentially with the feedback delay. The decay rate is amplified when the user is interference limited. Interference cancellation methods at the receiver are shown to mitigate the effect of interference. This work motivates the need for practical MIMO designs to overcome the adverse effects of interference. Second, limited feedback beamforming is analyzed on the downlink of a more realistic heterogeneous cellular network. Future generation cellular networks are expected to be heterogeneous, consisting of a mixture of macro base stations and low power nodes, to support the increasing user traffic capacity and reliability demand. Interference in heterogeneous environments cannot be coordinated using traditional interference mitigation techniques due to the on demand and random deployment of low power nodes such as femtocells. Using tools from stochastic geometry, the outage and average achievable rate of limited feedback MIMO is computed with same-tier and cross-tier interference, and feedback delay. A hybrid fixed and random network deployment model is used to analyze the performance in a fixed cell of interest. The maximum density of transmitting femtocells is derived as a function of the feedback rate and delay. The detrimental effect of same-tier interference is quantified, as the mobile user moves from the cell-center to the cell-edge. The third part of this dissertation considers limited coordination between randomly deployed transmitters. Building on the established degrading effect of uncoordinated interference on practical MIMO methods, and the analytical tractability of random deployment models, interference coordination is analyzed. Using multiple antennas at the transmitter for interference nulling in ad hoc networks is first shown to achieve MIMO gains using single antenna receivers. Clustered coordination is then investigated for cellular systems with randomly deployed base stations. As full coordination in the network is not feasible, a random clustering model is proposed where base stations located in the same cluster coordinate. The average achievable rate can be optimized as a function of the number of antennas to maximize the coordination gains. For multicell limited feedback, adaptive partitioning of feedback bits as a function of the signal and interference strength is proposed to minimize the loss in rate due to finite rate feedback.Item Self organizing networks : building traffic and environment aware wireless systems(2009-08) Rengarajan, Balaji; de Veciana, GustavoThis 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.Item Small cell and D2D offloading in heterogeneous cellular networks(2015-05) Ye, Qiaoyang; Andrews, Jeffrey G.; Caramanis, Constantine; Baccelli, Francois; Morton, David; Shakkottai, Sanjay; Vishwanath, SriramFuture wireless networks are evolving to become ever more heterogeneous, including small cells such as picocells and femtocells, and direct device-to-device (D2D) communication that bypasses base stations (BSs) altogether to share stored and personalized content. Conventional user association schemes are unsuitable for heterogeneous networks (HetNets), due to the massive disparities in transmit power and capabilities of different BSs. To make the most of the new low-power infrastructure and D2D communication, it is desirable to facilitate and encourage users to be offloaded from the macro BSs. This dissertation characterizes the gain in network performance (e.g., the rate distribution) from offloading users to small cells and the D2D network, and develops efficient user association, resource allocation, and interference management schemes aiming to achieve the performance gain. First, we optimize the load-aware user association in HetNets with single-antenna BSs, which bridges the gap between the optimal solution and a simple small cell biasing approach. We then develop a low-complexity distributed algorithm that converges to a near-optimal solution with a theoretical performance guarantee. Simulation results show that the biasing approach loses surprisingly little with appropriate bias factors, and there is a large rate gain for cell-edge users. This framework is then extended to a joint optimization of user association and resource blanking at the macro BSs – similar to the enhanced intercell interference coordination (eICIC) proposed in the global cellular standards, 3rd Generation Partnership Project (3GPP). Though the joint problem is nominally combinatorial, by allowing users to associate to multiple BSs, the problem becomes convex. We show both theoretically and through simulation that the optimal solution of the relaxed problem still results in a mostly unique association. Simulation shows that resource blanking can further improve the network performance. Next, the above framework with single-antenna transmission is extended to HetNets with BSs equipped with large-antenna arrays and operating in the massive MIMO regime. MIMO techniques enable the option of another interference management: serving users simultaneously by multiple BSs – termed joint transmission (JT). This chapter formulates a unified utility maximization problem to optimize user association with JT and resource blanking, exploring which an efficient dual subgradient based algorithm approaching optimal solutions is developed. Moreover, a simple scheduling scheme is developed to implement near-optimal solutions. We then change direction slightly to develop a flexible and tractable framework for D2D communication in the context of a cellular network. The model is applied to study both shared and orthogonal resource allocation between D2D and cellular networks. Analytical SINR distributions and average rates are derived and applied to maximize the total throughput, under an assumption of interference randomization via time and/or frequency hopping, which can be viewed as an optimized lower bound to other more sophisticated scheduling schemes. Finally, motivated by the benefits of cochannel D2D links, this dissertation investigates interference management for D2D links sharing cellular uplink resources. Showing that the problem of maximizing network throughput while guaranteeing the service of cellular users is non-convex and hence intractable, a distributed approach that is computationally efficient with minimal coordination is proposed instead. The key algorithmic idea is a pricing mechanism, whereby BSs optimize and transmit a signal depending on the interference to D2D links, who then play a best response (i.e., selfishly) to this signal. Numerical results show that our algorithms converge quickly, have low overhead, and achieve a significant throughput gain, while maintaining the quality of cellular links at a predefined service level.Item Transmission strategies for wireless multiple-antenna relay-assisted networks(2012-05) Truong, Kien Trung; Heath, Robert W., Ph. D.; Evans, Brian L.; Humphreys, Todd E.; Nettles, Scott; Sanghavi, SujayGlobal mobile data traffic has more than doubled in the past four years, and will only increase throughout the upcoming years. Modern cellular systems are striving to enable communications at high data rates over wide geographical areas to meet the surge in data demand. This requires advanced technologies to mitigate fundamental effects of wireless communications like path-loss, shadowing, small-scale fading, and interference. Two of such technologies are: i) deploying multiple antennas at the transmitter and receiver, and ii) employing an extra radio, called the relay, to forward messages from the transmitter to the receiver. The advantages of both technologies can be leveraged by using multiple antennas at the relay, transmitter, and receiver. Multiple-antenna relay-assisted communication is emerging as one promising technique for expanding the overall capacity of cellular networks. Taking full advantage of multiple-antenna relay-assisted cellular systems requires transmission strategies for jointly configuring the transmitters and receivers based on knowledge of the wireless propagation medium. This dissertation proposes such transmission strategies for wireless multiple-antenna relay-assisted systems. Two popular types of relays are considered: i) amplify-and-forward relays (the relays simply apply linear signal processing to their observed signals before retransmitting) and ii) decode-and-forward relays (the relays decode their observed signals and then re-encode before retransmitting). The first part of this dissertation considers the three-node multiple-antenna amplify-and-forward relay channel. Algorithms for adaptively selecting the number of data streams and subsets of transmit antennas at the transmitter and relay to provide reliable transmission at a guaranteed rate are proposed. Expressions for extracting spatial characteristics of the end-to-end multiple-antenna relay channel are derived. The second part of the dissertation presents interference management strategies that are developed specifically for two models of multiple-antenna relay interference channels where a number of relays assist multiple transmitters to communicate with multiple receivers. One model uses amplify-and-forward relays while the other uses decode-and-forward relays. Based on the idea of interference alignment, these strategies aim at maximizing the sum of achievable end-to-end rates. Simulation results show that the proposed transmission strategies with multiple-antenna relays achieve higher capacity and reliability than both those without relays and those with single-antenna relays.