Feedback Allocation For OFDMA Systems With Slow Frequency-domain Scheduling

We study the problem of allocating limited feedback resources across multiple users in an orthogonal-frequency-division-multiple-access downlink system with slow frequency-domain scheduling. Many flavors of slow frequency-domain scheduling (e.g., persistent scheduling, semi-persistent scheduling), that adapt user-sub-band assignments on a slower time-scale, are being considered in standards such as 3GPP Long-Term Evolution. In this paper, we develop a feedback allocation algorithm that operates in conjunction with any arbitrary slow frequency-domain scheduler with the goal of improving the throughput of the system. Given a user-sub-band assignment chosen by the scheduler, the feedback allocation algorithm involves solving a weighted sum-rate maximization at each (slow) scheduling instant. We first develop an optimal dynamic-programming-based algorithm to solve the feedback allocation problem with pseudo-polynomial complexity in the number of users and in the total feedback bit budget. We then propose two approximation algorithms with complexity further reduced, for scenarios where the problem exhibits additional structure.Comment: Accepted to IEEE Transactions on Signal Processin

Enhanced Gas-Liquid Absorption Utilizing Micro-Structured Surfaces and Fluid Delivery Systems

Despite intensive research and development efforts in renewable energy in recent years, more than 80% of the energy supply in the year 2040 is expected to come from fossil fuel-based sources. Increasing anthropogenic greenhouse gas emissions led the United States to legislatively limit domestic CO2 emissions to between 1000-1100 lb/MWh for new fossil fuel-fired power plants, thus creating an urgent need for efficient gas separation (capture) processes. Meanwhile, the gradual replacement of coal with cleaner burning natural gas will introduce additional challenges of its own since nearly 40% of the world's gas reserves are sour due to high concentrations of corrosive and toxic H2S and CO2 gases, both of which are to be separated. Next-generation micro-structured reactors for industrial mass and heat transfer processes are a disruptive technology that could yield substantial process intensification, size reduction, increased process control and safety. This dissertation proposes a transformative gas separation solution utilizing advanced micro-structured surfaces and gas delivery manifolds that serves to enhance gas separation processes. Experimental and numerical approaches have been used to achieve aggressive enhancements for a solvent-based CO2 absorption process. A laboratory-scale microreactor was investigated to fundamentally understand the physics of multiphase fluid flow with chemical reactions at the length scales under consideration. Reactor design parameters that promote rapid gas separation were studied. Computational fluid dynamics was used to develop inexpensive stationary (fixed) interface models for incorporation with optimization engines, as well as high fidelity unsteady (deforming) interface models featuring universal flow regime predictive capabilities. Scalability was investigated by developing a multiport microreactor and a stacked multiport microreactor that represented one and two orders magnitude increase in throughput, respectively. The present reactors achieved mass transfer coefficients as high as 400 1/s, which is between 2-4 orders of magnitude higher than conventional gas separation technologies and can be attributed to the impressive interfacial contact areas as high as 15,000 m2/m3 realized in this study through innovative design of the system. The substantial enhancement in performance achieved is indicative of the high level of process intensification that can be attained using the proposed micro-structured reactors for gas separation processes for diverse energy engineering applications. This dissertation is the first comprehensive work on the application of micro-structured surfaces and fluid delivery systems for gas separation and gas sweetening applications. More than ten refereed technical publications have resulted from this work, part of which has already been widely received by the community.&#8195

Infection, Transmission, Pathogenesis and Vaccine Development against Mycoplasma gallisepticum

Mycoplasma sp. comprises cell wall-less bacteria with reduced genome size and can infect mammals, reptiles, birds, and plants. Avian mycoplasmosis, particularly in chickens, is primarily caused by Mycoplasma gallisepticum (MG) and Mycoplasma synoviae. It causes infection and pathology mainly in the respiratory, reproductive, and musculoskeletal systems. MG is the most widely distributed pathogenic avian mycoplasma with a wide range of host susceptibility and virulence. MG is transmitted both by horizontal and vertical routes. MG infection induces innate, cellular, mucosal, and adaptive immune responses in the host. Macrophages aid in phagocytosis and clearance, and B and T cells play critical roles in the clearance and prevention of MG. The virulent factors of MG are adhesion proteins, lipoproteins, heat shock proteins, and antigenic variation proteins, all of which play pivotal roles in host cell entry and pathogenesis. Prevention of MG relies on farm and flock biosecurity, management strategies, early diagnosis, use of antimicrobials, and vaccination. This review summarizes the vital pathogenic mechanisms underlying MG infection and recapitulates the virulence factors of MG-host cell adhesion, antigenic variation, nutrient transport, and immune evasion. The review also highlights the limitations of current vaccines and the development of innovative future vaccines against MG

Controlled Decoding from Language Models

We propose controlled decoding (CD), a novel off-policy reinforcement learning method to control the autoregressive generation from language models towards high reward outcomes. CD solves an off-policy reinforcement learning problem through a value function for the reward, which we call a prefix scorer. The prefix scorer is used at inference time to steer the generation towards higher reward outcomes. We show that the prefix scorer may be trained on (possibly) off-policy data to predict the expected reward when decoding is continued from a partially decoded response. We empirically demonstrate that CD is effective as a control mechanism on Reddit conversations corpus. We also show that the modularity of the design of CD makes it possible to control for multiple rewards, effectively solving a multi-objective reinforcement learning problem with no additional complexity. Finally, we show that CD can be applied in a novel blockwise fashion at inference-time, again without the need for any training-time changes, essentially bridging the gap between the popular best-of-$K$ strategy and token-level reinforcement learning. This makes CD a promising approach for alignment of language models

The design of feedback channels for wireless networks : an optimization-theoretic view

textThe fundamentally fluctuating nature of the strength of a wireless link poses a significant challenge when seeking to achieve reliable communication at high data rates. Common sense, supported by information theory, tells us that one can move closer towards achieving higher data rates if the transmitter is provided with a priori knowledge of the channel. Such channel knowledge is typically provided to the transmitter by a feedback channel that is present between the receiver and the transmitter. The quality of information provided to the transmitter is proportional to the bandwidth of this feedback channel. Thus, the design of feedback channels is a key aspect in enabling high data rates. In the past, these feedback channels have been designed locally, on a link-by-link basis. While such an approach can be globally optimal in some cases, in many other cases, this is not true. In this thesis, we identify various settings in wireless networks, some already a part of existing standards, others under discussion in future standards, where the design of feedback channels is a problem that requires global, network-wide optimization. In general, we propose the treatment of feedback bandwidth as a network-wide resource, as the next step en route to achieving Gigabit wireless. Not surprisingly, such a global optimization initiative naturally leads us to the important issue of computational efficiency. Computational efficiency is critical from the point-of-view of a network provider. A variety of optimization techniques are employed in this thesis to solve the large combinatorial problems that arise in the context of feedback allocation. These include dynamic programming, sub-modular function maximization, convex relaxations and compressed sensing. A naive algorithm to solve these large combinatorial problems would typically involve searching over a exponential number of possibilities to find the optimal feedback allocation. As a general theme, we identify and exploit special application-specific structure to solve these problems optimally with reduced complexity. Continuing this endeavour, we search for more intricate structure that enables us to propose approximate solutions with significantly-reduced complexity. The accompanying analysis of these algorithms studies the inherent trade-offs between accuracy, efficiency and the required structure of the problem.Electrical and Computer Engineerin

Coupled thermoelastic analysis of fretting contacts

Fretting fatigue is the contact phenomenon occurring when two bodies in contact experience oscillatory loads. The surface tribology and contact stress evolution in a fretting contact has been studied using coupled thermoelastic analysis. Both, an aluminum and titanium alloy have been studied. Full-field real-time in-situ temperature maps of the contact region and its vicinity have been obtained using a multi-element infrared camera. The distinguishing features of the contact including the sliding regime, partial slip contact, bulk stress effects, boundary conditions effects etc. have been successfully captured using temperature measurement of the order of millikelvin. The coupled thermoclastic response of aluminum and titanium alloy has been successfully characterized, including the mean stress effect. A full coupled thermoelastic finite element model with Coulomb friction, frictional heating and gap conductance, has been used to predict the experimental temperatures. Changes in loads and changes in the coefficient of friction produce changes in different areas of the temperature field. The coupled thermoelastic effect may be used as a powerful tool to guide the march towards the complete understanding of the phenomenon of fretting. The method has been successfully used to guide the finite element analysis of a lap joint specimen