In this paper, we propose a relay selection amplify-and-forward (RS-AF) protocol in general bidirectional relay networks with two sources and N relays. In the proposed scheme, the two sources first ...simultaneously transmit to all the relays, and then, a single relay with a minimum sum symbol error rate (SER) will be selected to broadcast the received signals back to both sources. To facilitate the selection process, we propose a simple suboptimal min-max criterion for relay selection, where a single relay that minimizes the maximum SER of two source nodes will be selected. Simulation results show that the proposed min-max selection has almost the same performance as the optimal selection with lower complexity. We also present a simple asymptotic SER expression and make a comparison with the conventional all-participate AF relaying scheme. The analytical results are verified through simulations. To improve the system performance, optimal power allocation (OPA) between the sources and the relay is determined based on the asymptotic SER. Simulation results indicate that the proposed RS-AF scheme with OPA yields considerable performance improvement over an equal-power-allocation scheme, particularly with a large number of relay nodes.
In this paper, we consider a single-cell cellular network with a number of cellular users (CUs) and unmanned aerial vehicles (UAVs), in which multiple UAVs upload their collected data to the base ...station (BS). Two transmission modes are considered to support the multi-UAV communications, i.e., UAV-to-network (U2N) and UAV-to-UAV (U2U) communications. Specifically, the UAV with a high signal-to-noise ratio (SNR) for the U2N link uploads its collected data directly to the BS through U2N communication, while the UAV with a low SNR for the U2N link can transmit data to a nearby UAV through underlaying U2U communication for the sake of quality of service. We first propose a cooperative UAV sense-and-send protocol to enable the UAV-to-X communications, and then formulate the subchannel allocation and UAV speed optimization problem to maximize the uplink sum-rate. To solve this NP-hard problem efficiently, we decouple it into three sub-problems: U2N and cellular user (CU) subchannel allocation, U2U subchannel allocation, and UAV speed optimization. An iterative subchannel allocation and speed optimization algorithm (ISASOA) is proposed to solve these sub-problems jointly. The simulation results show that the proposed ISASOA can upload 10% more data than the greedy algorithm.
In this paper, we study the resource allocation and user scheduling problem for a downlink non-orthogonal multiple access network where the base station allocates spectrum and power resources to a ...set of users. We aim to jointly optimize the sub-channel assignment and power allocation to maximize the weighted total sum-rate while taking into account user fairness. We formulate the sub-channel allocation problem as equivalent to a many-to-many two-sided user-subchannel matching game in which the set of users and sub-channels are considered as two sets of players pursuing their own interests. We then propose a matching algorithm, which converges to a two-side exchange stable matching after a limited number of iterations. A joint solution is thus provided to solve the sub-channel assignment and power allocation problems iteratively. Simulation results show that the proposed algorithm greatly outperforms the orthogonal multiple access scheme and a previous non-orthogonal multiple access scheme.
In this paper, we study the user pairing in a downlink non-orthogonal multiple access (NOMA) network, where the base station allocates the power to the pairwise users within the cluster. In the ...considered NOMA network, a user with poor channel condition is paired with a user with good channel condition, when both their rate requirements are satisfied. Specifically, the quality of service for weak users can be guaranteed, since the transmit power allocated to strong users is constrained following the concept of cognitive radio. A distributed matching algorithm is proposed in the downlink NOMA network, aiming to optimize the user pairing and power allocation between weak users and strong users, subject to the users' targeted rate requirements. Our results show that the proposed algorithm outperforms the conventional orthogonal multiple access scheme and approaches the performance of the centralized algorithm, despite its low complexity. In order to improve the system's throughput, we design a practical adaptive turbo trellis coded modulation scheme for the considered network, which adaptively adjusts the code rate and the modulation mode based on the instantaneous channel conditions. The joint design work leads to significant mutual benefits for all the users as well as the improved system throughput.
In this letter, we consider an unmanned aerial vehicle (UAV) relay network, where the UAV works as an amplify-and-forward relay. We optimize the trajectory of UAV, the transmit power of UAV, and the ...mobile device by minimizing the outage probability of this relay network. The analytical expression of outage probability is derived first. A closed-form low-complexity solution with joint trajectory design and power control is proposed to solve this non-convex problem. Simulation results show that the outage probability of the proposed solution is significantly lower than that of the fixed power relay and circle trajectory for the UAV relay.
Device-to-device communication underlaying cellular networks allows mobile devices such as smartphones and tablets to use the licensed spectrum allocated to cellular services for direct peer-to-peer ...transmission. D2D communication can use either one-hop transmission (i.e. D2D direct communication) or multi-hop clusterbased transmission (i.e. in D2D local area networks). The D2D devices can compete or cooperate with each other to reuse the radio resources in D2D networks. Therefore, resource allocation and access for D2D communication can be treated as games. The theories behind these games provide a variety of mathematical tools to effectively model and analyze the individual or group behaviors of D2D users. In addition, game models can provide distributed solutions to the resource allocation problems for D2D communication. The aim of this article is to demonstrate the applications of game-theoretic models to study the radio resource allocation issues in D2D communication. The article also outlines several key open research directions.
Device-to-device (D2D) communication underlaying cellular networks is expected to bring significant benefits for utilizing resources, improving user throughput, and extending the battery life of user ...equipment. However, the allocation of radio and power resources to D2D communication needs elaborate coordination, as D2D communication can cause interference to cellular communication. In this paper, we study joint channel and power allocation to improve the energy efficiency of user equipments. To solve the problem efficiently, we introduce an iterative combinatorial auction algorithm, where the D2D users are considered bidders that compete for channel resources and the cellular network is treated as the auctioneer. We also analyze important properties of D2D underlay communication and present numerical simulations to verify the proposed algorithm.
Device-to-device (D2D) communication, which enables direct communication between nearby mobile devices, is an attractive add-on component to improve spectrum efficiency and user experience by reusing ...licensed cellular spectrum in 5G system. In this paper, we propose to enable D2D communication in unlicensed spectrum (D2D-U) as an underlay of the uplink LTE network for further booming the network capacity. A sensing-based protocol is designed to support the unlicensed channel access for both LTE and D2D users. We further investigate the subchannel allocation problem to maximize the sum rate of LTE and D2D users while considering their interference to the existing Wi-Fi systems. Specifically, we formulate the subchannel allocation as a many-to-many matching problem with externalities, and develop an iterative user-subchannel swap algorithm. Analytical and simulation results show that the proposed D2D-U scheme can significantly improve the system sum rate.
Device-to-device (D2D) communication is viewed as one promising technology for boosting the capacity of wireless networks and the efficiency of resource management. D2D communication heavily depends ...on the participation of users in sharing contents. Thus, it is imperative to introduce new incentive mechanisms to motivate such user involvement. In this paper, a contract-theoretic approach is proposed to solve the problem of providing incentives for D2D communication in cellular networks. First, using the framework of contract theory, the users' preferences toward D2D communication are classified into a finite number of types, and the service trading between the base station and users is properly modeled. Next, necessary and sufficient conditions are derived to provide incentives for users' engagement in D2D communication. Finally, our analysis is extended to the case in which there is a continuum of users. Simulation results show that the contract can effectively incentivize users' participation, and increase capacity of the cellular network than the other mechanisms.
In the current unmanned aircraft systems (UASs) for sensing services, unmanned aerial vehicles (UAVs) transmit their sensory data to terrestrial mobile devices over the unlicensed spectrum. However, ...the interference from surrounding terminals is uncontrollable due to the opportunistic channel access. In this paper, we consider a cellular Internet of UAVs to guarantee the Quality-of-Service (QoS), where the sensory data can be transmitted to the mobile devices either by UAV-to-Device (U2D) communications over cellular networks, or directly through the base station (BS). Since UAVs' sensing and transmission may influence their trajectories, we study the trajectory design problem for UAVs in consideration of their sensing and transmission. This is a Markov decision problem (MDP) with a large state-action space, and thus, we utilize multi-agent deep reinforcement learning (DRL) to approximate the state-action space, and then propose a multi-UAV trajectory design algorithm to solve this problem. Simulation results show that our proposed algorithm can achieve a higher total utility than policy gradient algorithm and single-agent algorithm.
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