The University of Maryland, College Park, founded in 1856, is a distinguished public research university. It is the largest university in Maryland and the Washington metropolitan area, and is located nine miles from downtown Washington, D.C. It is a public research university offering over 200 degree-granting programs across its eleven schools and colleges, attracting top students and renowned faculty from around the world. It is known for its innovative and challenging academic programs, strong research opportunities, and a vibrant multicultural community. NEC Labs America collaborates with the University of Maryland, College Park, on research spanning edge AI, distributed systems, machine learning interpretability, learning with limited labels, domain adaptation, and continual learning. Our research improves model generalization in dynamic conditions. We jointly study robust inference, communication-efficient federated learning, and privacy-aware analytics for large-scale deployments. Please read about our latest news and collaborative publications with the University of Maryland, College Park.

Posts

Channel Reciprocity Calibration for Hybrid Beamforming in Distributed MIMO Systems

/in /by

Time Division Duplex (TDD)-based distributed massive MIMO systems are envisioned as candidate solution for the physical layer of 6G multi-antenna systems supporting cooperative hybrid beamforming that heavily relies on the obtained uplink channel estimates for efficient coherent downlink precoding. However, due to the hardware impairment between the transmitter and the receiver, full channel reciprocity does not hold between the downlink and uplink direction. Such reciprocity mismatch deteriorates the performance of mm-Wave hybrid beamforming and has to be estimated and compensated for, to avoid performance degradation in the co-operative hybrid beamforming. In this paper, we address the channel reciprocity calibration between any two nodes at two levels. We decompose the problem into two sub-problems. In the first sub-problem, we calibrate the digital chain, i.e. obtain the mismatch coefficients of the (DAC/ADC) up to a constant scaling factor. In the second subproblem, we obtain the (PA/LNA) mismatch coefficients. At each step, we formulate the channel reciprocity calibration as a least square optimization problem that can efficiently be solved via conventional methods such as alternative optimization with high accuracy. Finally, we verify the performance of our channel reciprocity calibration approach through extensive numerical experiments.

Read more

The Trade-off between Scanning Beam Penetration and Transmission Beam Gain in mmWave Beam Alignment

/in /by

Beam search algorithms have been proposed to align the beams from an access point to a user equipment. The process relies on sending beams from a set of scanning beams (SB) and tailoring a transmission beam (TB) using the received feedback. In this paper, we discuss a fundamental trade-off between the gain of SBs and TBs. The higher the gain of an SB, the better the penetration of the SB and the higher the gain of the TB the better the communication link performance. However, TB depends on the set of SBs and by increasing the coverage of each SB and in turn reducing its penetration, there is more opportunity to find a sharper TB to increase its beamforming gain. We define a quantitative measure for such trade-off in terms of a trade-off curve. We introduce SB set design namely Tulip design and formally prove it achieves this fundamental trade-off curve for channels with a single dominant path. We also find closed-form solutions for the trade-off curve for special cases and provide an algorithm with its performance evaluation results to find the trade-off curve revealing the need for further optimization on the SB sets in the state-of-the-art beam search algorithms.

Read more

Application-specific, Dynamic Reservation of 5G Compute and Network Resources by using Reinforcement Learning

/in /by

5G services and applications explicitly reserve compute and network resources in today’s complex and dynamic infrastructure of multi-tiered computing and cellular networking to ensure application-specific service quality metrics, and the infrastructure providers charge the 5G services for the resources reserved. A static, one-time reservation of resources at service deployment typically results in extended periods of under-utilization of reserved resources during the lifetime of the service operation. This is due to a plethora of reasons like changes in content from the IoT sensors (for example, change in number of people in the field of view of a camera) or a change in the environmental conditions around the IoT sensors (for example, time of the day, rain or fog can affect data acquisition by sensors). Under-utilization of a specific resource like compute can also be due to temporary inadequate availability of another resource like the network bandwidth in a dynamic 5G infrastructure. We propose a novel Reinforcement Learning-based online method to dynamically adjust an application’s compute and network resource reservations to minimize under-utilization of requested resources, while ensuring acceptable service quality metrics. We observe that a complex application-specific coupling exists between the compute and network usage of an application. Our proposed method learns this coupling during the operation of the service, and dynamically modulates the compute and network resource requests to mimimize under-utilization of reserved resources. Through experimental evaluation using real-world video analytics application, we show that our technique is able to capture complex compute-network coupling relationship in an online manner i.e. while the application is running, and dynamically adapts and saves up to 65% compute and 93% network resources on average (over multiple runs), without significantly impacting application accuracy.

Read more

Codebook Design for Hybrid Beamforming in 5G Systems

/in /by

Massive MIMO and hybrid beamforming are among the key physical layer technologies for the next generation wireless systems. In the last stage of the hybrid beamforming, the goal is to generate sharp beam with maximal and preferably uniform gain. We highlight the shortcomings of uniform linear arrays (ULAs) in generating such perfect beams, i.e., beams with maximal uniform gain and sharp edges, and propose a solution based on a novel antenna configuration, namely, twin-ULA (TULA). Consequently, we propose two antenna configurations based on TULA: Delta and Star. We pose the problem of finding the beamforming coefficients as a continuous optimization problem for which we find the analytical closed-form solution by a quantization/aggregation method. Thanks to the derived closed-form solution the beamforming coefficients can be easily obtained with low complexity. Through numerical analysis, we illustrate the effectiveness of the proposed antenna structure and beamforming algorithm to reach close-to-perfect beams.

Read more

ROMA: Resource Orchestration for Microservices-based 5G Applications

/in /by

With the growth of 5G, Internet of Things (IoT), edge computing and cloud computing technologies, the infrastructure (compute and network) available to emerging applications (AR/VR, autonomous driving, industry 4.0, etc.) has become quite complex. There are multiple tiers of computing (IoT devices, near edge, far edge, cloud, etc.) that are connected with different types of networking technologies (LAN, LTE, 5G, MAN, WAN, etc.). Deployment and management of applications in such an environment is quite challenging. In this paper, we propose ROMA, which performs resource orchestration for microservices-based 5G applications in a dynamic, heterogeneous, multi-tiered compute and network fabric. We assume that only application-level requirements are known, and the detailed requirements of the individual microservices in the application are not specified. As part of our solution, ROMA identifies and leverages the coupling relationship between compute and network usage for various microservices and solves an optimization problem in order to appropriately identify how each microservice should be deployed in the complex, multi-tiered compute and network fabric, so that the end-to-end application requirements are optimally met. We implemented two real-world 5G applications in video surveillance and intelligent transportation system (ITS) domains. Through extensive experiments, we show that ROMA is able to save up to 90%, 55% and 44% compute and up to 80%, 95% and 75% network bandwidth for the surveillance (watchlist) and transportation application (person and car detection), respectively. This improvement is achieved while honoring the application performance requirements, and it is over an alternative scheme that employs a static and overprovisioned resource allocation strategy by ignoring the resource coupling relationships.

Read more

Codebook Design for Composite Beamforming in Next-generation mmWave Systems

/in /by

In pursuance of the unused spectrum in higher frequencies, millimeter wave (mmWave) bands have a pivotal role. However, the high path-loss and poor scattering associated with mmWave communications highlight the necessity of employing effective beamforming techniques. In order to efficiently search for the beam to serve a user and to jointly serve multiple users it is often required to use a composite beam which consists of multiple disjoint lobes. A composite beam covers multiple desired angular coverage intervals (ACIs) and ideally has maximum and uniform gain (smoothness) within each desired ACI, negligible gain (leakage) outside the desired ACIs, and sharp edges. We propose an algorithm for designing such ideal composite codebook by providing an analytical closed-form solution with low computational complexity. There is a fundamental trade-off between the gain, leakage and smoothness of the beams. Our design allows to achieve different values in such trade-off based on changing the design parameters. We highlight the shortcomings of the uniform linear arrays (ULAs) in building arbitrary composite beams. Consequently, we use a recently introduced twin-ULA (TULA) antenna structure to effectively resolve these inefficiencies. Numerical results are used to validate the theoretical findings.

Read more

Multi-user Beam Alignment in Presence of Multi-path

/in /by

To overcome the high pathloss and the intense shadowing in millimeterwave (mmWave) communications, effective beamforming schemes are required which incorporate narrow beams with high beamforming gains. The mm Wave channel consists of a few spatial clusters each associated with an angle of departure (AoD). The narrow beams must be aligned with the channel AoDs to increase the beamforming gain. This is achieved through a procedure called beam alignment (BA). Most of the BA schemes in the literature consider channels with a single dominant path while in practice the channel has a few resolvable paths with different AoDs, hence, such BA schemes may not work correctly in the presence of multi-path or at the least do not exploit such multi path to achieve diversity or increase robustness. In this paper, we propose an efficient BA schemes in presence of multi-path. The proposed BA scheme transmits probing packets using a set of scanning beams and receives the feedback for all the scanning beams at the end of probing phase from each user. We formulate the BA scheme as minimizing the expected value of the average transmission beamwidth under different policies. The policy is defined as a function from the set of received feedback to the set of transmission beams (TB). In order to maximize the number of possible feedback sequences, we prove that the set of scanning beams (SB) has an special form, namely, Tulip Design. Consequently, we rewrite the minimization problem with a set of linear constraints and reduced number of variables which is solved by using an efficient greedy algorithm.

Read more

Multi user Beam Alignment in Presence of Multi path

/in /by

To overcome the high path loss and the intense shadowing in millimeter wave (mmWave) communications, effective beamforming schemes are required which incorporate narrow beams with high beamforming gains. The mmWave channel consists of a few spatial clusters each associated with an angle of departure (AoD). The narrow beams must be aligned with the channel AoDs to increase the beamforming gain. This is achieved through a procedure called beam alignment (BA). Most of the BA schemes in the literature consider channels with a single dominant path while in practice the channel has a few resolvable paths with different AoDs, hence, such BA schemes may not work correctly in the presence of multi path or at the least do not exploit such multipath to achieve diversity or increase robustness. In this paper, we propose an efficient BA scheme in presence of multi path. The proposed BA scheme transmits probing packets using a set of scanning beams and receives feedback for all the scanning beams at the end of the probing phase from each user. We formulate the BA scheme as minimizing the expected value of the average transmission beamwidth under different policies. The policy is defined as a function from the set of received feedback to the set of transmission beams (TB). In order to maximize the number of possible feedback sequences, we prove that the set of scanning beams (SB) has a special form, namely, Tulip Design. Consequently, we rewrite the minimization problem with a set of linear constraints and a reduced number of variables which is solved by using an efficient greedy algorithm.

Read more

Codebook Design for Composite Beamforming in Next generation mmWave Systems

/in /by

In pursuance of the unused spectrum in higher frequencies, millimeter wave (mmWave) bands have a pivotal role. However, the high path loss and poor scattering associated with mmWave communications highlight the necessity of employing effective beamforming techniques. In order to efficiently search for the beam to serve a user and to jointly serve multiple users it is often required to use a composite beam which consists of multiple disjoint lobes. A composite beam covers multiple desired angular coverage intervals (ACIs) and ideally has maximum and uniform gain (smoothness) within each desired ACI, negligible gain (leakage) outside the desired ACIs, and sharp edges. We propose an algorithm for designing such ideal composite codebook by providing an analytical closed form solution with low computational complexity. There is a fundamental trade off between the gain, leakage and smoothness of the beams. Our design allows to achieve different values in such trade off based on changing the design parameters. We highlight the shortcomings of the uniform linear arrays (ULAs) in building arbitrary composite beams. Consequently, we use a recently introduced twin ULA (TULA) antenna structure to effectively resolve these inefficiencies. Numerical results are used to validate the theoretical findings.

Read more

Shaping mmWave Wireless Channel via Multi-Beam Design using Reconfigurable Intelligent Surfaces

/in /by

Millimeter-wave (mmWave) communications is considered as a key enabler towards the realization of next-generation wireless networks, due to the abundance of available spectrum at mmWave frequencies. However, mmWave suffers from high free-space path-loss and poor scattering resulting in mostly line-of-sight (LoS) channels which result in a lack of coverage. Reconfigurable intelligent surfaces (RIS), as a new paradigm, have the potential to fill the coverage holes by shaping the wireless channel. In this paper, we propose a novel approach for designing RIS with elements arranged in a uniform planar array (UPA) structure. In what we refer to as multi-beamforming, We propose and design RIS such that the reflected beam comprises multiple disjoint lobes. Moreover, the beams have optimized gain within the desired angular coverage with fairly sharp edges avoiding power leakage to other regions. We provide a closed-form low-complexity solution for the multi-beamforming design. We confirm our theoretical results by numerical analysis.

Read more