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1. Description of the objectives and motivation for the contribution to ECE education The demand for wireless data transmission capacity is increasing rapidly and this growth is expected to continue due to ongoing prevalence of cellular phones and new and emerging bandwidth-intensive applications that encompass high-definition video, unmanned aerial systems (UAS), intelligent transportation systems (ITS) including autonomous vehicles, and others. Meanwhile, vital military and public safety applications also depend on access to the radio frequency spectrum. To meet these demands, the US federal government is beginning to move from the proven but inefficient model of exclusive frequency assignments to a more-efficient, shared-spectrum approach in some bands of the radio frequency spectrum. A STEM workforce that understands the radio frequency spectrum and applications that use the spectrum is needed to further increase spectrum efficiency and cost-effectiveness of wireless systems over the next several decades to meet anticipated and unanticipated increases in wireless data capacity. 2. Relevant background including literature search examples if appropriate CISCO Systems’ annual survey indicates continued strong growth in demand for wireless data capacity. Meanwhile, undergraduate electrical and computer engineering courses in communication systems, electromagnetics, and networks tend to emphasize mathematical and theoretical fundamentals and higher-layer protocols, withmore »
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As several new spectrum bands are opening up for shared use, a new paradigm of Diverse Band-aware Dynamic Spectrum Access (d-DSA) has emerged. d-DSA equips a secondary device with software defined radios (SDRs) and utilize whitespaces (or idle channels) in multiple bands, including but not limited to TV, LTE, Citizen Broadband Radio Service (CBRS), unlicensed ISM. In this paper, we propose a decentralized, online multi-agent reinforcement learning based cross-layer BAnd selection and Routing Design (BARD) for such d-DSA networks. BARD not only harnesses whitespaces in multiple spectrum bands, but also accounts for unique electro-magnetic characteristics of those bands to maximize the desired quality of service (QoS) requirements of heterogeneous message packets; while also ensuring no harmful interference to the primary users in the utilized band. Our extensive experiments demonstrate that BARD outperforms the baseline dDSAaR algorithm in terms of message delivery ratio, however, at a relatively higher network latency, for varying number of primary and secondary users. Furthermore, BARD greatly outperforms its single-band DSA variants in terms of both the metrics in all considered scenarios.
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Current cellular systems use pilot-aided statistical channel state information (S-CSI) estimation and limited feedback schemes to aid in link adaptation and scheduling decisions. However, in the presence of pulsed radar signals, pilot-aided S-CSI is inaccurate since interference statistics on pilot and nonpilot resources can be different. Moreover, the channel will be bimodal as a result of the periodic interference. In this paper, we propose a max-min heuristic to estimate the post-equalizer SINR in the case of non-pilot pulsed radar interference, and characterize its distribution as a function of noise variance and interference power. We observe that the proposed heuristic incurs low computational complexity, and is robust beyond a certain SINR threshold for different modulation schemes, especially for QPSK. This enables us to develop a comprehensive semi-blind framework to estimate the wideband SINR metric that is commonly used for S-CSI quantization in 3GPP Long-Term Evolution (LTE) and New Radio (NR) networks. Finally, we propose dual CSI feedback for practical radar-cellular spectrum sharing, to enable accurate CSI acquisition in the bimodal channel. We demonstrate significant improvements in throughput, block error rate and retransmission-induced latency for LTE-Advanced Pro when compared to conventional pilot-aided S-CSI estimation and limited feedback schemes.
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In this paper, we consider an underlay radar-massive MIMO spectrum sharing scenario in which massive MIMO base stations (BSs) with elevation beamforming capabilities are allowed to operate outside a circular exclusion zone centered at the radar. Modeling the locations of the massive MIMO BSs as a homogeneous Poisson point process (PPP), we derive an analytical expression for a tight upper bound on the average interference at the radar due to cellular transmissions. The challenge lies in bounding the worst-case elevation angle for each massive MIMO BS, for which we devise a novel construction based on the circumradius distribution of a typical Poisson-Voronoi (PV) cell. While these worst-case elevation angles are correlated for neighboring BSs due to the structure of the PV tessellation, it does not explicitly appear in our analysis because of our focus on the average interference.We also provide an estimate of the nominal average interference by approximating each cell as a circle with area equal to the average area of the typical cell. Using these results, we demonstrate that the gap between the two results remains approximately constant with respect to the exclusion zone radius. Our analysis reveals useful trends in average interference power, as a function ofmore »
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In December 2017, the Third Generation Partnership Project (3GPP) released the first set of specifications for 5G New Radio (NR), which is currently the most widely accepted 5G cellular standard. 5G NR is expected to replace LTE and previous generations of cellular technology over the next several years, providing higher throughput, lower latency, and a host of new features. Similar to LTE, the 5G NR physical layer consists of several physical channels and signals, most of which are vital to the operation of the network. Unfortunately, like for any wireless technology, disruption through radio jamming is possible. This paper investigates the extent to which 5G NR is vulnerable to jamming and spoofing, by analyzing the physical downlink and uplink control channels and signals. We identify the weakest links in the 5G NR frame, and propose mitigation strategies that should be taken into account during implementation of 5G NR chipsets and base stations.