查看更多>>摘要：In this paper, we propose a novel composition aided generalized quadrature spatial modulation (C-GQSM) scheme to improve the spectral efficiency (SE) of the GQSM systems by exploiting the power domain degree of freedom. The C-GQSM scheme constitutes a hybridization of GQSM and composition modulation (CM) principles, allowing the information bits to encompass not only the antenna activation patterns (AAPs) and amplitude/phase modulated (APM) constellation symbols, but also the energy allocation patterns (EAPs). In addition, we present two low-complexity detection techniques for the proposed C-GQSM system. The first one is based on the ordered successive interference cancellation (OSIC) technique, while the other based on the weighted coordinate descent (WCD) algorithm. Moreover, the upper bound of the average bit error probability (ABEP) of the proposed C-GQSM scheme is derived under both uncorrelated and correlated channel conditions. Simulation results show that the proposed C-GQSM outperforms both the conventional CM and GQSM systems in terms of SE without sacrificing the bit error rate (BER) performance.
Gaurav DuggalR. Michael BuehrerHarpreet S. DhillonJeffrey H. Reed...
3653-3668页
查看更多>>摘要：Wireless positioning in Non-Line-of-Sight (NLoS) scenarios presents significant challenges due to multipath effects that lead to biased measurements and reduced positioning accuracy. This paper revisits electromagnetic field theory related to diffraction and in the context of wireless positioning and proposes a novel positioning technique that greatly improves accuracy in NLoS environments dominated by diffraction. The method is applied to a critical public safety use case: precisely locating at-risk individuals within buildings, with a particular focus on improving 3D positioning and z-axis accuracy. By leveraging the Geometrical Theory of Diffraction (GTD), the approach introduces an innovative NLoS path length model and a new NLOS positioning technique. Using Fisher information analysis, we establish the conditions required for 3D positioning and derive lower bounds on positioning performance for both 3D and z-axis estimates for the proposed NLOS positioning technique. Additionally, we propose an algorithmic implementation of the proposed NLoS positioning method using non-linear least squares estimation, which we term D-NLS. The positioning performance of our proposed NLOs positioning technique is validated using an extensive ray-tracing simulation. The numerical results highlight the superiority of our approach in outdoor-to-indoor environments, which directly estimates NLoS path lengths and delivers significant performance enhancements over existing methods for both 3D and z-axis positioning scenarios.
查看更多>>摘要：Cell-free wireless networks have garnered significant interest within the research community due to their potential to eliminate cell-edge effects and exploit macro-diversity. In this paper, we design algorithms to jointly optimize uplink transmit powers and dynamic user-centric clusters within a cell-free network. This strategy aims to effectively mitigate inter-user interference and attain spectral efficiency targets for users in a scalable manner. To serve this goal, we re-purpose a classic iterative algorithm and prove its convergence for both the maximum ratio combiner (MRC) and linear minimum mean square error (LMMSE) receivers. We present several access point (AP) subset selection schemes of varying complexity and demonstrate how clustering requirements differ according to receiver capabilities. In particular, we show that optimizing the serving cluster for each user is crucial when using the simple MRC receiver.
查看更多>>摘要：Although the semantic communication with joint semantic-channel coding design has shown promising performance in transmitting data of different modalities over physical layer channels, the synchronization and packet-level forward error correction (FEC) of multimodal semantics have not been well studied. Synchronizing multimodal features in both the semantic and time domains is challenging due to the independent design of semantic encoders. In this paper, we take the facial video and speech transmission as an example and propose a Synchronous Multi-modal Semantic Communication System with Packet-Level Coding (SyncSC). To achieve semantic and time synchronization, 3D Morphable Mode (3DMM) coefficients and text are transmitted as semantics. We propose a semantic codec that achieves similar reconstruction quality with lower bandwidth. The visual-guided speech synthesis is designed to synchronize video, text and speech. We propose a packet-Level FEC method for video semantics, called PacSC, that maintains visual quality even at high packet loss rates. For text packets, a text packet loss concealment module, called TextPC, based on Bidirectional Encoder Representations from Transformers (BERT) is proposed, which improves the performance of traditional FEC methods. Simulation results show that SyncSC reduces transmission overhead while ensuring high-quality synchronous transmission of video and speech over the packet loss network.
查看更多>>摘要：Wi-Fi channel measurements across different bands, e.g., sub-7-GHz and 60-GHz bands, are asynchronous due to the uncoordinated nature of distinct standards protocols, e.g., 802.11ac/ax/be and 802.11ad/ay. Multi-band Wi-Fi fusion has been considered before on a frame-to-frame basis for simple classification tasks, which does not require fine-time-scale alignment. In contrast, this paper considers asynchronous sequence-to-sequence fusion between sub-7-GHz channel state information (CSI) and 60-GHz beam signal-to-noise-ratio (SNR)s for more challenging tasks, such as continuous coordinate estimation. To handle the timing disparity between asynchronous multi-band Wi-Fi channel measurements, this paper proposes a multi-band neural dynamic fusion (NDF) framework. This framework uses separate encoders to embed the multi-band Wi-Fi measurement sequences to separate initial latent conditions. Using a continuous-time ordinary differential equation (ODE) modeling, these initial latent conditions are propagated to the respective latent states of the multi-band channel measurements at the same time instances for a latent alignment and a post-ODE fusion, and at their original time instances for measurement reconstruction. We derive a customized loss function based on the variational evidence lower bound (ELBO) that balances between the multi-band measurement reconstruction and continuous coordinate estimation. We evaluate the NDF framework using an in-house multi-band Wi-Fi testbed and demonstrate substantial performance improvements over a comprehensive list of single-band and multi-band baseline methods.
查看更多>>摘要：Task offloading is a promising approach to efficiently realize delay-sensitive, computation-intensive applications in Internet of Vehicles (IoVs). However, task allocation and scheduling pose great challenges in Vehicular Fog Computing (VFC) environment due to resource heterogeneity, workload unpredictability, fixed Fog Access Points (F-APs), and the dynamic nature of fog environment. This paper investigates the delay- and energy-efficient task offloading strategy in Cell Free massive MIMO (CF-mMIMO)-enabled VFC network. CF-mMIMO system is integrated into the VFC network so that task transfer among F-APs is enabled. A Long Short Term Memory (LSTM)-based algorithm is designed to predict the workload of F-APs. Based on the result, the delay and energy consumption of a task if it is offloaded on a F-AP can be calculated. After that, a Multi-Agent Deep Deterministic Policy Gradient (MADDPG)-based algorithm is developed to explore the best combination of task offloading and resource allocation strategies to reduce the overhead of each vehicle, and to minimize the long-term system cost, eventually. Simulation results show that the proposed strategy not only exhibits good convergence performance in scenario which involves a mixture of continuous-discrete action spaces, but also achieves satisfying performance in terms of average cost under varied circumstances.
查看更多>>摘要：In this paper, we explore the integration of low-power, low-cost stacked intelligent metasurfaces (SIM) into cell-free (CF) massive multiple-input multiple-output (mMIMO) systems to enhance access point (AP) capabilities and address high power consumption and cost challenges. Specifically, we investigate the uplink performance of a SIM-enhanced CF mMIMO system and propose a novel system framework. First, the closed-form expressions of the spectral efficiency (SE) are obtained using the unique two-layer signal processing framework of CF mMIMO systems. Second, to mitigate inter-user interference, an interference-based greedy algorithm for pilot allocation is introduced. Third, a wave-based beamforming algorithm for SIM is proposed, based only on statistical channel state information, which effectively reduces the fronthaul costs. Finally, two different power control algorithms are proposed to improve the performance of UE with inferior channel conditions. The results indicate that increasing the number of SIM layers and meta-atoms leads to significant performance improvements and allows for a reduction in the number of APs and AP antennas, thus lowering the costs. In particular, the best SE performance is achieved with the deployment of 20 APs plus 1200 SIM meta-atoms. Finally, the proposed wave-based beamforming algorithm can enhance the SE performance of SIM-enhanced CF-mMIMO systems by 57%, significantly outperforming traditional CF mMIMO systems.
NETL
NSTL
IEEE