The performance of systems where multiple users communicate over wireless fading links benefits from channel-adaptive allocation of the available resources. Different from most existing approaches that allocate resources based on perfect channel state information, this work optimizes channel scheduling along with per user rate and power loadings over orthogonal fading channels, when both terminals and scheduler rely on quantized channel state information. Channel-adaptive policies are designed to optimize an average transmit-performance criterion subject to average quality of service requirements. While the resultant optimal policy per fading realization shows that the individual rate and power loadings can be obtained separately for each user, the optimal scheduling is slightly more complicated. Specifically, per fading realization each channel is allocated either to a single (winner) user, or, to a small group of winner users whose percentage of shared resources is found by solving a linear program. A single scheduling scheme combining both alternatives becomes possible by smoothing the original disjoint scheme. The smooth scheduling is asymptotically optimal and incurs reduced computational complexity. Different alternatives to obtain the Lagrange multipliers required to implement the channel-adaptive policies are proposed, including stochastic iterations that are provably convergent and do not require knowledge of the channel distribution. The development of the optimal channel-adaptive allocation is complemented with discussions on the overhead required to implement the novel policies.
This paper presents a quantized Kalman filter implemented using unreliable memories. We consider that both the quantization and the unreliable memories introduce errors in the computations, and develop an error propagation model that takes into account these two sources of errors. In addition to providing updated Kalman filter equations, the proposed error model accurately predicts the covariance of the estimation error and gives a relation between the performance of the filter and its energy consumption, depending on the noise level in the memories. Then, since memories are responsible for a …
Optimizing Learned Image Compression on Scalar and Entropy-Constraint Quantization
Fraunhofer Institute for Telecommunications – Heinrich Hertz Institute（弗劳恩霍夫电信研究所——海因里希·赫兹研究所）；Institute of Computer Science（计算机科学研究所）；Free University of Berlin（柏林自由大学）；Department of Telecommunication Systems（电信系统系）
In this paper, we investigate for the first time the dynamic power allocation and decoding order at the base station (BS) of two-user uplink (UL) cooperative non-orthogonal multiple access (C-NOMA)-based cellular networks. In doing so, we formulate a joint optimization problem aiming at maximizing the minimum user achievable rate, which is a non-convex optimization problem and hard to be directly solved. To tackle this issue, an iterative algorithm based on successive convex approximation (SCA) is proposed. The numerical results reveal that the proposed scheme provides superior performance in …
This paper investigates the sum spectral efficiency maximization problem in downlink multiuser multiple-input multiple-output (MIMO) systems with low-resolution quantizers at an access point (AP) and users. In particular, we consider rate-splitting multiple access (RSMA) to enhance spectral efficiency by offering opportunities to boost achievable degrees of freedom. Optimizing RSMA precoders, however, is highly challenging due to the minimum rate constraint when determining the rate of the common stream. The quantization errors coupled with the precoders further make the problem more complicat…
An intelligent reflecting surface (IRS) can greatly improve the channel quality over a frequency-flat channel, if it is configured to reflect the incident signal as a beam towards the receiver. However, the fundamental limitations of the IRS technology become apparent over practical frequency-selective channels, where the same configuration must be used over the entire bandwidth. In this paper, we consider a wideband orthogonal frequency-division multiplexing (OFDM) system that is supported by a fairly realistic IRS setup with two unbalanced states per element and also mutual coupling. We desc…
This paper investigates the benefits of integrating reconfigurable intelligent surface (RIS) on minimizing the average sum age of information (AoI) in uplink non-orthogonal multiple access-based Internet-of-Things (IoT) networks. In this setup, an optimization problem is formulated to optimize the RIS configuration, the transmit power per IoT device and the clustering policy of IoT devices. The formulated problem is a mixed-integer non-convex one, and in order to solve it we obtain first the RIS configuration by adopting a semi-definite relaxation (SDR) approach. Afterwards, the joint power al…
Intelligent reflecting surface (IRS)-enabled backscatter communications can be enabled by an access point (AP) that splits its transmit signal into modulated and unmodulated parts. This letter integrates non-orthogonal multiple access (NOMA) with this method to create a two-user primary system and a secondary system of IRS data. Considering the decoding order, we maximize the rate of the strongest primary user by jointly optimizing the IRS phase shifts, power splitting (PS) factor at the AP, and NOMA power coefficients while guaranteeing the quality of service (QoS) for both weak user and IRS …
VQ-DSC-R: Robust Vector Quantized-Enabled Digital Semantic Communication With OFDM Transmission
ZGC Institute of Ubiquitous-X Innovation and Applications（ubiquitous-X 创新与应用研究所）；Beijing Key Laboratory of 6G DOICT converged and Cloud-Native Mobile Information Networks（北京6G DOICT融合与云原生移动信息网络重点实验室）；State Key Laboratory of Networking and Switching Technology（网络与交换技术国家重点实验室）；Beijing University of Posts and Telecommunications（北京邮电大学）
End-to-End NOMA with Perfect and Quantized CSI Over Rayleigh Fading Channels
Department of ECE, Villanova University（电子工程系，维拉文纳大学）；Electrical Engineering and Computer Science, University of California, Irvine（电气工程与计算机科学，加州大学伊文斯顿分校）
This paper considers downlink of reconfigurable intelligent surface (RIS) assisted cooperative non-orthogonal multiple access (CNOMA) systems. Our objective is to minimize the total transmit power by jointly optimizing the active beamforming vectors, transmit-relaying power, and RIS phase shifts. The formulated problem is a mixed-integer nonlinear programming (MINLP) problem. To tackle this problem, the alternating optimization approach is utilized to decouple the variables. In each alternative procedure, the optimal solutions for the active beamforming vectors, transmit-relaying power and pha…
This paper considers a wireless network with a base station (BS) conducting timely status updates to multiple clients via adaptive non-orthogonal multiple access (NOMA)/orthogonal multiple access (OMA). Specifically, the BS is able to adaptively switch between NOMA and OMA for the downlink transmission to optimize the information freshness of the network, characterized by the Age of Information (AoI) metric. If the BS chooses OMA, it can only serve one client within each time slot and should decide which client to serve; if the BS chooses NOMA, it can serve more than one client at the same tim…
