- Read more about Single RF Chain Hybrid Analog/Digital Beamforming for mmWave Massive-MIMO
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Hybrid beamforming has attracted considerable attention in recent years as an efficient and promising technique for the practical implementation of millimeter-Wave (mmWave) massive multiple-input multiple-output (MIMO) wireless systems. In this paper, we investigate hybrid analog/digital beamforming designs based on a single RF chain architecture (SRCA) for mmWave massive-MIMO. We first revisit the SRCA and then explore its shortcomings.
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- Read more about Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications
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- Read more about Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering
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Power delay profiles (PDPs) are an important factor in the design of wireless networks, e.g., in choosing the length of a cyclic prefix. While distributed networks are receiving increasing attention, the impact of cooperation on the PDP has not been addressed. We address this issue in this paper. Specifically, we analyze a network where each user is served by a cluster of Remote Radio Heads (RRHs) with RRH locations modeled as a Poisson point process.
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- Read more about Data Driven QoE-QoS Association Modeling of Conversational Video
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In recent years, the variety and volume of multimedia services have increased exponentially. Like most of other multimedia services, the conversational video service has stringent quality of service and experience requirements. In order to better support users QoE (Quality of Experience) and allocate network resources more effectively, this paper focuses on the QoS (Quality of Service)-QoE association modeling of conversational video flows.
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- Read more about Joint Subchannel and Power Allocation for Cognitive NOMA Systems with Imperfect CSI
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In this paper, a robust power allocation and subchannel assignment algorithm was proposed to maximize the total EE
of SUs for cognitive NOMA systems under taking channel uncertainties and diverse QoS requirements of users into account. The RAA problem was formulated into a non-convex mixed-integer fractional programming problem with the outage probabilities of users and thus difficult to solve. Based on Gaussian CSI error models, we transformed the robust rate constraint and the robust interference power constraint into the convex constraints. By slacking the integer subchannel allocation factor into a continuous variable, the original problem was converted into a convex problem by using the subtractive-form auxiliary variable. Based on the Lagrangian dual approach and the subgradient updating methods, the closed-form solutions were obtained. The effectiveness of the proposed algorithm was verified by comparing it with the existing algorithms.
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- Read more about MEMORY-BASED PARAMETERIZED SKILLS LEARNING FOR MAPLESS VISUAL NAVIGATION
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The recently-proposed reinforcement learning for mapless visual navigation can generate an optimal policy for searching different targets. However, most state-of-the-art deep reinforcement learning (DRL) models depend on hard rewards to learn the optimal policy, which can lead to the lack of previous diverse experiences. Moreover, these pre-trained DRL models cannot generalize well to un-trained tasks. To overcome these problems above, in this paper, we propose a Memorybased Parameterized Skills Learning (MPSL) model for mapless visual navigation.
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Consider a network with N nodes in d dimensions, and M overlapping subsets P_1,...,P_M (subnetworks). Assume that the nodes in a given P_i are observed in a local coordinate system. We wish to register the subnetworks using the knowledge of the observed coordinates. More precisely, we want to compute the positions of the N nodes in a global coordinate system, given P_1,...,P_M and the corresponding local coordinates. Among other applications, this problem arises in divide-and-conquer algorithms for localization of adhoc sensor networks.
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- Read more about Detection of Pilot-Hopping Sequences for Grant-Free Random Access in Massive MIMO Systems
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- Read more about CHANNEL IMPULSIVE NOISE MITIGATION FOR LINEAR VIDEO CODING SCHEMES
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The problem of impulse noise mitigation is considered when videos encoded using a SoftCast based Linear Video Coding scheme are transmitted using an OFDM scheme over a wideband channel prone to impulse noise A Fast Bayesian Matching Pursuit algorithm is employed for impulse noise mitigation This approach requires the provisioning of some OFDM subchannels to estimate the impulse noise locations and amplitudes Provisioned subchannels cannot be used to transmit data and lead to a decrease of the nominal decoded video quality at receivers in absence of impulse noise Using a phenomenological mod
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- Read more about ON ACHIEVABLE RATES FOR MASSIVE MIMO SYSTEM WITH IMPERFECT CHANNEL COVARIANCE INFORMATION
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