In this paper, we study the resource allocation problem for a single-cell non-orthogonal multiple access (NOMA) relay network where an OFDM amplify-and-forward relay allocates the spectrum and power ...resources to the source-destination (SD) pairs. We aim to optimize the resource allocation to maximize the average sum-rate. The optimal approach requires an exhaustive search, leading to an NP-hard problem. To solve this problem, we propose two efficient many-to-many two-sided SD pair-subchannel matching algorithms, in which the SD pairs and sub-channels are considered as two sets of players chasing their own interests. The proposed algorithms can provide a sub-optimal solution to this resource allocation problem in affordable time. Both the static matching algorithm and the dynamic matching algorithm converge to a pair-wise stable matching after a limited number of iterations. Simulation results show that the capacity of both proposed algorithms in the NOMA scheme significantly outperforms the conventional orthogonal multiple access scheme. The proposed matching algorithms in NOMA scheme also achieve a better user-fairness performance than the conventional orthogonal multiple access.
Recently, the intelligent omni-surface (IOS) has been proposed as a novel instance of metasurface to achieve full-dimensional communications by jointly engineering its reflective and refractive ...properties. However, optimal beamforming scheme for the IOS is hard to obtain due to the difficulty in acquiring perfect channel state information (CSI). To address this issue, in this paper, we consider an IOS aided system where the beamforming scheme is designed via beam training with codebooks at the base station (BS), the IOS, and users. Given that the refractive/reflective signals are closely related to both incident signals from the BS and phase shifts of IOS elements, the codebooks at the BS and the IOS are designed jointly. Based on the joint BS-IOS codebook, a multi-lobe beam training mechanism is proposed to perform beam training for multiple users simultaneously, thereby reducing the training overhead. The training/feedback overhead of the proposed beam training and the impact of the codebook size are then analyzed theoretically. Simulation results indicate that the proposed scheme achieves a higher sum rate than the state-of-the-art beam training schemes and performs close to the perfect CSI case.
Holographic Multiple Input Multiple Output (HMIMO), which integrates massive antenna elements into a compact space to achieve a spatially continuous aperture, plays an important role in future ...wireless networks. With numerous antenna elements, it is hard to implement the HMIMO via phased arrays due to unacceptable power consumption. To address this issue, reconfigurable refractive surface (RRS) is an energy-efficient enabler of HMIMO since the surface is free of expensive phase shifters. Unlike traditional metasurfaces working as passive relays, the RRS is used as transmit antennas, where the far-field approximation does not hold anymore, urging a new performance analysis framework. In this letter, we first derive the data rate of an RRS-based single-user downlink system, and then compare its power consumption with the phased array. Simulation results verify our analysis and show that the RRS is an energy-efficient way to HMIMO.
In this paper, we consider a cooperative autonomous driving system where a vehicle overtakes the one in front based on collective perception. To avoid collisions with vehicles on the other lane, we ...propose a V2X-based cooperative collision avoidance scheme. The overtaking vehicle estimates the distance between itself and the neighbors via V2V communications and decides whether to overtake or not. Two cases where the distance information is obtained independently and cooperatively are taken into account. We derive the probability of collision avoidance and analyze the influence of different factors such as speed and density of vehicles on the system performance. Simulation results verify our analysis and show that our V2X-based cooperative collision avoidance scheme performs better than traditional GNSS-based collision avoidance scheme. The performance gain brought by the cooperative case compared to the independent case in our scheme can also be observed.
Using widely deployed Internet of Things (IoT) sensors to perceive the environmental distribution is crucial in many IoT applications, such as intelligent healthcare and smart home. As using ...traditional sensors will lead to high costs and maintenance, it is important to design the next-generation IoT sensor to reduce the cost of ubiquitous deployment. For this purpose, we propose a novel IoT system based on low-cost and fully passive meta-material sensors. Specifically, the meta-material sensors can sense multiple environmental conditions such as temperature and humidity levels, and transmit back the information by signal reflection, simultaneously. With the information contained in the received signals, a wireless receiver can obtain detailed environmental distributions. However, it is not trivial to achieve high sensing accuracy in the meta-material sensor based IoT system because the structure of the meta-materials, the deployment positions of sensors, and the reconstruction function for environmental distributions need to be jointly optimized. To handle this challenge, we propose an algorithm to design the meta-material based IoT system with the help of a deep learning approach. Simulation results verify that the proposed algorithm effectively maximizes the sensing accuracy. Experimental evaluations also show that the proposed scheme can obtain humidity distribution with an accuracy of over 93%.
In the coming 6G communications, the internet of things (IoT) will be a fundamental enabler for ubiquitous environment perception, which requires the IoT sensors to consume near-zero power and have ...the lowest cost. For this purpose, the IoT sensors are expected to perform simultaneous sensing and transmission, so that energy and hardware costs due to signal modulation can be saved. In this paper, we propose the concept of meta-IoT, i.e., the IoT with sensors composed of specially designed meta-materials, which can achieve simultaneous sensing and transmission without supplied power. The basic idea of meta-IoT sensors is that the signal reflection on the sensors is sensitive to environmental conditions, which can be captured by a wireless receiver. In order to optimize the sensing systems with meta-IoT sensors, we establish the mathematical model of meta-IoT sensors' sensing and transmission and then jointly optimize the sensors' structure and the environment estimation at the receiver. We design and implement a practical meta-IoT sensing system for monitoring temperature and humidity levels. Simulation results show that the proposed technique can obtain the optimal sensor structure, and the experimental results verify that the designed meta-IoT sensing system achieves low measurement errors.
Recently, reconfigurable intelligent surfaces (RISs) have been proposed as a novel solution to enhance wireless communications such as suppressing inter-cell interference. However, signals arriving ...at a conventional reflecting-type RIS can only be reflected towards one side, leading to a limited service coverage, especially in an indoor environment involving potential obstacles. In this paper, we consider an intelligent omni-surface (IOS) which can provide services for users on both sides by enabling simultaneous signal reflection and transmission. Specifically, we propose an IOS aided indoor communication system where an IOS is embedded in a wall between two independent access points (APs) to suppress inter-cell interference. Due to the independence of the APs, we design a distributed hybrid beamforming scheme consisting of digital beamforming at APs and IOS-based analog beamforming to maximize the sum rate without any exchange of channel state information (CSI) between APs. Simulation results indicate that the proposed system performs very close to an optimal centralized scheme, and has a better sum rate performance compared to existing schemes.
Intelligent omni-surfaces (IOS) have attracted great attention recently due to its potential to achieve full-dimensional communications by simultaneously reflecting and refracting signals toward both ...sides of the surface. However, it still remains an open question whether the reciprocity holds between the uplink and downlink channels in the IOS-aided wireless communications. In this work, we first present a physics-compliant IOS-related channel model, based on which the channel reciprocity is investigated. We then demonstrate the angle-dependent electromagnetic response of the IOS element in terms of both incident and departure angles. This serves as the key feature of IOS that drives our analytical results on beam non-reciprocity. Finally, simulation and experimental results are provided to verify our theoretical analyses.
Wireless simultaneous localization and mapping (SLAM) has attracted much attention as a promising technique to empower location based services. However, the accuracy of traditional wireless SLAM ...systems is limited as the wireless signals are easily disturbed by the uncontrollable radio environments. To mitigate this issue, in this paper, we propose a MetaSLAM system where multiple reconfigurable intelligent surfaces (RISs) are deployed to customize the wireless environments. To be specific, through adjusting the phase shifts of these RISs, the strength of reflected signals can be enhanced in order to resist the variance of radio environments. However, it is challenging to coordinate multiple RISs and optimize their phase shifts especially when their locations are unknown to the agent. In order to address these challenges, we formulate a MetaSLAM optimization problem, and design a two-stage optimization algorithm based on the genetic and particle filter algorithms to solve the formulated problem. Analysis of the complexity and the positioning error bound of the proposed SLAM system are provided. Simulation results show that compared with the benchmark schemes, the positioning error obtained by the MetaSLAM system is reduced by at least 31%.
In this letter, we study the integrated satellite-terrestrial network where users can access the core network by the backhaul links via both multi-layer satellites in the space and terrestrial access ...points on the ground. The mega-constellation design for such an integrated satellite-terrestrial network is investigated to realize the global seamless connectivity and provide high-rate backhaul transmission. First, we propose a theoretical framework for the average uplink capacity analysis. Second, based on the developed theoretical framework, we design a mega satellite constellation given the capacity of terrestrial backhaul links for realizing the global connectivity with the minimum satellite number. Simulation results show that as the terrestrial infrastructures are distributed more evenly in latitude, the designed mega-constellation first requires more satellites and then remains unchanged regardless of the terrestrial transmission capacity of high-latitude user terminals.
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