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Weidong Mei

Publications and source records attributed to Weidong Mei.

104 records · Page 6Linked to original sources

Uplink Cooperative Interference Cancellation for Cellular-Connected UAV: A Quantize-and-Forward Approach

Aerial-ground interference is the main obstacle to achieving high spectral efficiency in cellular networks with both traditional terrestrial users and new unmanned aerial vehicle (UAV) users. Due to their strong line-of-sight (LoS) channels with the ground, UAVs could cause/suffer severe interference to/from a large number of non-associated but co-channel base stations (BSs) in their uplink/downlink communications. In this letter, we propose a new cooperative interference cancellation (CIC) scheme for the UAV's uplink communication to mitigate its strong interference to co-channel BSs, which requires only local cooperation between each co-channel BS and its adjacent helping BSs. Specifically, the helping BSs without serving any users in the UAV's communication channel quantize and forward their received signals from the UAV to their aided co-channel BS, which then processes the quantized signals jointly with its own received signal to decode its served terrestrial user's message via canceling the UAV's signal by linear/nonlinear interference cancellation techniques (ICTs). We derive the achievable rates of the proposed CIC scheme with different ICTs as a function of the UAV's transmit power and rate, and thereby unveil the conditions under which the proposed CIC scheme outperforms the existing CIC scheme based on the decode-and-forward (DF) operation of the helping BSs.

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Cooperative NOMA for Downlink Asymmetric Interference Cancellation

This letter advances the non-orthogonal multiple access (NOMA) technique for cellular downlink co-channel interference mitigation, via exploiting the (limited) cooperation among base stations (BSs). Specifically, we consider a simplified but practically relevant scenario of two co-channel cells with asymmetric interference, i.e., only the user in one cell receives the strong interference from the BS in the other cell. To mitigate such interference, we propose a new cooperative NOMA scheme, where the interfered user's serving BS sends a superposed signal comprising both the desired message and the co-channel user's message (shared by the interfering BS). The co-channel user's signal is aimed to add constructively with the interfering BS's signal at the interfered user's receiver so that the combined interference with enhanced power can be effectively decoded and cancelled. This thus leads to a new problem on how to optimally allocate the transmit power for the two superposed messages. We provide the closed-form solution to this problem and investigate the conditions under which the performance of the proposed scheme is superior over the existing schemes.

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UAV-Sensing-Assisted Cellular Interference Coordination: A Cognitive Radio Approach

Aerial-ground interference mitigation has been deemed as the main challenge in realizing cellular-connected unmanned aerial vehicle (UAV) communications. Due to the line-of-sight (LoS)-dominant air-ground channels, the UAV generates/suffers much stronger interference to/from cellular base stations (BSs) over a much larger region in its uplink/downlink communication, as compared to the terrestrial users. As a result, conventional inter-cell interference coordination (ICIC) techniques catered for terrestrial networks become ineffective in mitigating the more severe UAV-induced interference. To deal with this new challenge, this letter introduces a cognitive radio based solution by treating the UAV and terrestrial users as secondary and primary users in the network, respectively. In particular, the LoS channels with terrestrial BSs/users endow the UAV with a powerful spectrum sensing capability for detecting the terrestrial signals over a much larger region than its serving BS. By exploiting this unique feature, we propose a new UAV-sensing-assisted ICIC design for both the UAV downlink and uplink communications. Specifically, the UAV senses its received interference and the transmissions of terrestrial users in the downlink and uplink, respectively, over the resource blocks (RBs) available at its serving BS to assist its RB allocation to the UAV for avoiding the interference with co-channel terrestrial communications. Numerical results demonstrate that the proposed UAV-assisted ICIC outperforms the conventional terrestrial ICIC by engaging the neighboring BSs for cooperation only.

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A New Store-then-Amplify-and-Forward Protocol for UAV Mobile Relaying

In this letter, we consider the use of an unmanned aerial vehicle (UAV) as a mobile relay to assist the communication between two ground users without a direct link. We propose a novel store-then-amplify-and-forward (SAF) relaying protocol for the UAV to exploit its mobility jointly with the low-complexity AF relaying. Specifically, the received signal from the source is first stored in a buffer at the UAV, then amplified and forwarded to the destination when the UAV flies closer to the destination. With this new SAF protocol, we aim to maximize the throughput of the UAV-enabled relaying system by jointly optimizing the source/UAV transmit power and the UAV trajectory, as well as the time-slot pairing for each data packet received and forwarded by the UAV. As this problem is a non-convex mixed integer optimization problem that is difficult to solve, we propose an efficient algorithm for obtaining a suboptimal solution for it by applying the techniques of Hungary algorithm, alternating optimization and successive convex approximation. Numerical results show that the proposed mobile SAF relaying outperforms the conventional AF relaying without signal storing.

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Cooperative Downlink Interference Transmission and Cancellation for Cellular-Connected UAV: A Divide-and-Conquer Approach

The line-of-sight dominant air-ground channels have posed critical interference issues in cellular-connected unmanned aerial vehicle (UAV) communications. In this paper, we propose a new base station (BS) cooperative beamforming (CB) technique for the cellular downlink to mitigate the strong interference caused by the co-channel terrestrial transmissions to the UAV. Besides the conventional CB by cooperatively transmitting the UAV's message, the serving BSs of the UAVs exploit a novel interference transmission scheme to effectively suppress the terrestrial interference to the UAV. Specifically, the co-channel terrestrial users' messages are shared with the UAV's serving BSs and transmitted via CB to cancel their resultant interference at the UAV. To balance between the CB gains for UAV signal enhancement and interference cancellation, we aim to maximize the UAV's receive signal-to-interference-plus-noise ratio by jointly optimizing the power allocations at all of its serving BSs for transmitting the UAV's and co-channel terrestrial users' messages. First, we derive the closed-form optimal solution to this problem in a special case and draw useful insights. Then, we propose an algorithm to solve the problem optimally in the general case. As the optimal solution requires centralized implementation with exorbitant message/channel information exchanges among the BSs, we further propose a distributed algorithm that is amenable to practical implementation, based on a new divide-and-conquer approach, whereby each co-channel BS divides its perceived interference to the UAV into multiple portions, each to be canceled by a different serving BS of the UAV with its best effort. Numerical results show that the proposed centralized and distributed CB schemes with interference transmission and cancellation (ITC) can both significantly outperform the conventional CB without applying ITC.

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Cellular-Connected UAV: Uplink Association, Power Control and Interference Coordination

The line-of-sight (LoS) air-to-ground channel brings both opportunities and challenges in cellular-connected unmanned aerial vehicle (UAV) communications. On one hand, the LoS channels make more cellular base stations (BSs) visible to a UAV as compared to the ground users, which leads to a higher macro-diversity gain for UAV-BS communications. On the other hand, they also render the UAV to impose/suffer more severe uplink/downlink interference to/from the BSs, thus requiring more sophisticated inter-cell interference coordination (ICIC) techniques with more BSs involved. In this paper, we consider the uplink transmission from a UAV to cellular BSs, under spectrum sharing with the existing ground users. To investigate the optimal ICIC design and air-ground performance trade-off, we maximize the weighted sum-rate of the UAV and existing ground users by jointly optimizing the UAV's uplink cell associations and power allocations over multiple resource blocks. However, this problem is non-convex and difficult to be solved optimally. We first propose a centralized ICIC design to obtain a locally optimal solution based on the successive convex approximation (SCA) method. As the centralized ICIC requires global information of the network and substantial information exchange among an excessively large number of BSs, we further propose a decentralized ICIC scheme of significantly lower complexity and signaling overhead for implementation, by dividing the cellular BSs into small-size clusters and exploiting the LoS macro-diversity for exchanging information between the UAV and cluster-head BSs only. Numerical results show that the proposed centralized and decentralized ICIC schemes both achieve a near-optimal performance, and draw important design insights based on practical system setups.

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Safeguarding Wireless Network with UAVs: A Physical Layer Security Perspective

Integrating unmanned aerial vehicles (UAVs) into future wireless systems such as the fifth-generation (5G) cellular network is anticipated to bring significant benefits for both UAV and telecommunication industries. Generally speaking, UAVs can be used as new aerial platforms in the cellular network to provide communication services for terrestrial users, or become new aerial users of the cellular network served by the terrestrial base stations. Due to their high altitude, UAVs usually have dominant line-of-sight (LoS) channels with the ground nodes, which, however, pose new security challenges to future wireless networks with widely deployed UAVs. On one hand, UAV-ground communications are more prone than terrestrial communications to eavesdropping and jamming attacks by malicious nodes on the ground. On the other hand, compared to malicious ground nodes, malicious UAVs can launch more effective eavesdropping and jamming attacks to terrestrial communications. Motivated by the above, in this article, we aim to identify such new issues from a physical-layer security viewpoint and propose novel solutions to tackle them efficiently. Numerical results are provided to validate their effectiveness and promising directions for future research are also discussed.

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Cognitive UAV Communication via Joint Maneuver and Power Control

This paper investigates a new scenario of spectrum sharing between unmanned aerial vehicle (UAV) and terrestrial wireless communication, in which a cognitive/secondary UAV transmitter communicates with a ground secondary receiver (SR), in the presence of a number of primary terrestrial communication links that operate over the same frequency band. We exploit the UAV's mobility in three-dimensional (3D) space to improve its cognitive communication performance while controlling the co-channel interference at the primary receivers (PRs), such that the received interference power at each PR is below a prescribed threshold termed as interference temperature (IT). First, we consider the quasi-stationary UAV scenario, where the UAV is placed at a static location during each communication period of interest. In this case, we jointly optimize the UAV's 3D placement and power control to maximize the SR's achievable rate, subject to the UAV's altitude and transmit power constraints, as well as a set of IT constraints at the PRs to protect their communications. Next, we consider the mobile UAV scenario, in which the UAV is dispatched to fly from an initial location to a final location within a given task period. We propose an efficient algorithm to maximize the SR's average achievable rate over this period by jointly optimizing the UAV's 3D trajectory and power control, subject to the additional constraints on UAV's maximum flying speed and initial/final locations. Finally, numerical results are provided to evaluate the performance of the proposed designs for different scenarios, as compared to various benchmark schemes. It is shown that in the quasi-stationary scenario the UAV should be placed at its minimum altitude while in the mobile scenario the UAV should adjust its altitude along with horizontal trajectory, so as to maximize the SR's achievable rate in both scenarios.

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Uplink Cooperative NOMA for Cellular-Connected UAV

Aerial-ground interference mitigation is a challenging issue in the cellular-connected unmanned aerial vehicle (UAV) communications. Due to the strong line-of-sight (LoS) air-to-ground (A2G) channels, the UAV may impose/suffer more severe uplink/downlink interference to/from the cellular base stations (BSs) than the ground users. To tackle this challenge, we propose to apply the non-orthogonal multiple access (NOMA) technique to the uplink communication from a UAV to cellular BSs, under spectrum sharing with the existing ground users. However, for our considered system, traditional NOMA with local interference cancellation (IC), termed non-cooperative NOMA, may provide very limited gain compared to the OMA. This is because there are many co-channel BSs due to the LoS A2G channels and thus the UAV's rate performance is severely limited by the BS with the worst channel condition with the UAV. To improve the UAV's achievable rate, a new cooperative NOMA scheme is proposed by exploiting the backhaul links among BSs. Specifically, some BSs with better channel conditions are selected to decode the UAV's signals first, and then forward the decoded signals to their backhaul-connected BSs for IC. To investigate the optimal design of cooperative NOMA, we maximize the weighted sum-rate of the UAV and ground users by jointly optimizing the UAV's rate and power allocations over multiple resource blocks. However, this problem is hard to be solved optimally. To obtain useful insights, we first consider two special cases with egoistic and altruistic transmission strategies of the UAV, respectively, and solve their corresponding problems optimally. Next, we consider the general case and propose an efficient suboptimal solution via the alternating optimization. Numerical results show that the proposed cooperative NOMA yields significant throughput gains than the OMA and the non-cooperative NOMA benchmark.

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Physical Layer Service Integration in 5G: Potentials and Challenges

High transmission rate and secure communication have been identified as the key targets that need to be effectively addressed by fifth generation (5G) wireless systems. In this context, the concept of physical-layer security becomes attractive, as it can establish perfect security using only the characteristics of wireless medium. Nonetheless, to further increase the spectral efficiency, an emerging concept, termed physical-layer service integration (PHY-SI), has been recognized as an effective means. Its basic idea is to combine multiple coexisting services, i.e., multicast/broadcast service and confidential service, into one integral service for one-time transmission at the transmitter side. This article first provides a tutorial on typical PHY-SI models. Furthermore, we propose some state-of-the-art solutions to improve the overall performance of PHY-SI in certain important communication scenarios. In particular, we highlight the extension of several concepts borrowed from conventional single-service communications, such as artificial noise (AN), eigenmode transmission etc., to the scenario of PHY-SI. These techniques are shown to be effective in the design of reliable and robust PHY-SI schemes. Finally, several potential research directions are identified for future work.

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Artificial Noise-Aided Biobjective Transmitter Optimization for Service Integration in Multi-User MIMO Gaussian Broadcast Channel

This paper considers an artificial noise (AN)-aided transmit design for multi-user MIMO systems with integrated services. Specifically, two sorts of service messages are combined and served simultaneously: one multicast message intended for all receivers and one confidential message intended for only one receiver and required to be perfectly secure from other unauthorized receivers. Our interest lies in the joint design of input covariances of the multicast message, confidential message and artificial noise (AN), such that the achievable secrecy rate and multicast rate are simultaneously maximized. This problem is identified as a secrecy rate region maximization (SRRM) problem in the context of physical-layer service integration. Since this bi-objective optimization problem is inherently complex to solve, we put forward two different scalarization methods to convert it into a scalar optimization problem. First, we propose to prefix the multicast rate as a constant, and accordingly, the primal biobjective problem is converted into a secrecy rate maximization (SRM) problem with quality of multicast service (QoMS) constraint. By varying the constant, we can obtain different Pareto optimal points. The resulting SRM problem can be iteratively solved via a provably convergent difference-of-concave (DC) algorithm. In the second method, we aim to maximize the weighted sum of the secrecy rate and the multicast rate. Through varying the weighted vector, one can also obtain different Pareto optimal points. We show that this weighted sum rate maximization (WSRM) problem can be recast into a primal decomposable form, which is amenable to alternating optimization (AO). Then we compare these two scalarization methods in terms of their overall performance and computational complexity via theoretical analysis as well as numerical simulation, based on which new insights can be drawn.

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On Artificial-Noise Aided Transmit Design for Multi-User MISO Systems with Integrated Services

This paper considers artificial noise (AN)-aided transmit designs for multi-user MISO systems in the eyes of service integration. Specifically, we combine two sorts of services, and serve them simultaneously: one multicast message intended for all receivers and one confidential message intended for only one receiver. The confidential message is kept perfectly secure from all the unauthorized receivers. Our goal is to jointly design the optimal input covariances for the multicast message, confidential message and AN, such that the achievable secrecy rate region is maximized subject to the sum power constraint. This secrecy rate region maximization (SRRM) problem is a nonconvex vector maximization problem. To handle it, we reformulate the SRRM problem into a provably equivalent scalar optimization problem and propose a searching method to find all of its Pareto optimal points. The equivalent scalar optimization problem is identified as a secrecy rate maximization (SRM) problem with the quality of multicast service (QoMS) constraints. Further, we show that this equivalent QoMS-constrained SRM problem, albeit nonconvex, can be efficiently handled based on a two-stage optimization approach, including solving a sequence of semidefinite programs. Moreover, we also extend the SRRM problem to an imperfect channel state information (CSI) case where a worst-case robust formulation is considered. In particular, while transmit beamforming is generally a suboptimal technique to the SRRM problem, we prove that it is optimal for the confidential message transmission whether in the perfect CSI scenario or in the imperfect CSI scenario. Finally, numerical results demonstrate that the AN-aided transmit designs are effective in expanding the achievable secrecy rate regions.

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Transmit design for MIMO wiretap channel with a malicious jammer

In this paper, we consider the transmit design for multi-input multi-output (MIMO) wiretap channel including a malicious jammer. We first transform the system model into the traditional three-node wiretap channel by whitening the interference at the legitimate user. Additionally, the eavesdropper channel state information (ECSI) may be fully or statistically known, even unknown to the transmitter. Hence, some strategies are proposed in terms of different levels of ECSI available to the transmitter in our paper. For the case of unknown ECSI, a target rate for the legitimate user is first specified. And then an inverse water-filling algorithm is put forward to find the optimal power allocation for each information symbol, with a stepwise search being used to adjust the spatial dimension allocated to artificial noise (AN) such that the target rate is achievable. As for the case of statistical ECSI, several simulated channels are randomly generated according to the distribution of ECSI. We show that the ergodic secrecy capacity can be approximated as the average secrecy capacity of these simulated channels. Through maximizing this average secrecy capacity, we can obtain a feasible power and spatial dimension allocation scheme by using one dimension search. Finally, numerical results reveal the effectiveness and computational efficiency of our algorithms.

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GSVD-Based Precoding in MIMO Systems With Integrated Services

This letter considers a two-receiver multiple-input multiple-output (MIMO) Gaussian broadcast channel model with integrated services. Specifically, we combine two sorts of service messages, and serve them simultaneously: one multicast message intended for both receivers and one confidential message intended for only one receiver. The confidential message is kept perfectly secure from the unauthorized receiver. Due to the coupling of service messages, it is intractable to seek capacity-achieving transmit covariance matrices. Accordingly, we propose a suboptimal precoding scheme based on the generalized singular value decomposition (GSVD). The GSVD produces several virtual orthogonal subchannels between the transmitter and the receivers. Subchannel allocation and power allocation between multicast message and confidential message are jointly optimized to maximize the secrecy rate in this letter, subject to the quality of multicast service (QoMS) constraints. Since this problem is inherently complex, a difference-of-concave (DC) algorithm, together with an exhaustive search, is exploited to handle the power allocation and subchannel allocation, respectively. Numerical results are presented to illustrate the efficacy of our proposed strategies.

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