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Since autonomous underwater vehicles (AUVs) are increasing popular in maritime applications, underwater wireless communication with multiple users is becoming more important and practical. In this paper, we investigate the resource allocation in underwater acoustic networks (UAN) with time division multiple access (TDMA) technique. When the uncertain channel state information (CSI) derived from the movement of AUVs in underwater environment is considered, probability constraints are introduced to guarantee the quality of service (QoS). A joint optimization algorithm is proposed, in order to schedule time for energy harvesting (EH) and wireless information transfer (WIT); the proposed algorithm also allocates transmit power to multiple AUVs to maximize the sum-throughput over a time period. The constraints of outage probability and available energy are both considered. The probability constraint is first transformed into an equivalent formulation. Furthermore, an approach with low computational complexity is proposed for power allocation and time assignment based on the residual energy of the buoy. In extensive simulation experiments, the proposed algorithm shows significant throughput increases in long term compared to baseline schemes, and better performance in terms of convergence and energy efficiency (EE) can be achieved. [ABSTRACT FROM AUTHOR]

In this paper, the resource scheduling and power control strategy is studied for a two-tier 5G network system, which is comprised of a central macrocell and several small cells. Because cellular deployment is ultra dense in the 5G network, a sleep strategy for small cells is proposed to reduce energy consumption caused by the cellular overlapping coverage. Specifically, the imperfect channel state information (CSI) is considered due to the complex and dynamic communication environment in practice. This work attempts to maximize the resource utilization and enhance the robustness of the power control strategy with imperfect CSI. An optimization problem with probability constraints is formulated, and the high rate requirements of 5G network users are included. A novel method is provided to convert probability constraints into deterministic ones. An iterative algorithm of power control to enhance the network efficiency is proposed further. Finally, numerical results are given to illustrate the effectiveness of the joint resource scheduling scheme. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communications in a cellular network can be implemented on vehicular communications. However, high mobilities of vehicles generate fast channel variations in the communications. Channel description has to be specified in the D2D-enable vehicular communications network. In this paper, the vehicle speed and the sampling time are involved to the channel description such that the dynamic information of vehicle is integrated with the channel gain. By doing so, the channel description is more practical. The power control and spectrum sharing problem is formulated in order to maximize the energy-efficiency (EE) of total vehicle-to-infrastructure (V2I) links. It also attempts to ensure reliable communications in a multi-cellular users multi-D2D users frequency division multiple access (FDMA) cellular environment. The reformulated objective function in the fractional form is proved to be quasi-concave, and it can be solved by the Dinkelbach method which requires low computational complexity. In addition, the Hungarian algorithm is used to determine the optimal match of cellular user equipments (CUEs) and V2V pairs. User fairness is further considered under the goal of maximizing overall energy efficiency. Then, the approach of minimum EE maximization is implemented on all V2I links in order to improve system fairness. Finally, the system performance of the proposed scheme is validated by numerical simulations. The results show that the algorithm is effective to improve the energy efficiency and robustness in the dynamic communications environment. [ABSTRACT FROM AUTHOR]

In cellular networks, proximity users establish device-to-device(D2D) links directly under the control of base stations (BSs) for data exchange, and no base station forwarding is required. For the advantages such as lower transmission power, higher data transmission rate, D2D communication has been paid more and more attention. However, the environmental impact of introducing D2D shared spectrum resources has become a major challenge. This paper studies a robust downlink power control scheme with imperfect channel state information (CSI) in D2D communication system. In order to improve the system sum rates, this paper optimizes the transmitting power of D2D users (DUEs) and the base stations through geometric analysis and convex optimization while guaranteeing the quality-of-service (QoS) requirements for both DUEs and cellular users (CUEs). Because of the dynamic characteristics of wireless channel, it is difficult and expensive to acquire CSI without direct communication with BS. On this account, we consider channel uncertainty rather than perfect or instantaneous known CSI. Aiming at enhancing the system robustness, we formulate an outage-based robust optimization problem. The original deterministic the signal-to-interference-noise-ratio (SINR) constraints are substituted with the transformed probability constraints, which transforms the random channel gain into a deterministic one with outage threshold. The simulation results show that the power allocation based on the proposed algorithm can adapt to the complex channel environment and are with better robustness. [ABSTRACT FROM AUTHOR]

Underwater positioning and tracking scheme for non-cooperative objects is of great essence to explore unknown fields. Due to the high response time and non-line-of-sight(NLOS) propagation in the underwater acoustic sensor networks (UASNs), the existed range-based 3D target tracking algorithms are generally inaccurate on detecting underwater non-cooperative objects. In order to solve the problems above, the corresponding solutions are presented respectively in this paper. Although it is hard to change the inherent property of the underwater acoustic propagation, reducing the communication time is another way to solve the problem indirectly. Since the ranging phase and synchronize phase occupy most of the communication time, the presented novel ranging scheme for non-cooperative objects reduces the redundant time consumption, and further eliminates the necessity of synchronization process in advanced. For NLOS propagation, a distributed residual weighting discrimination (DRWD) algorithm based on grouping strategy is proposed for non-cooperative objects. The position estimations of the groups containing the NLOS link error are always distributed in isolation, and the estimations without the NLOS link errors are always concentrated in a small range. According to this feature, a low computational complexity approach namely two-step least square (LS) is proposed to determine the best location by analyzing the distribution of estimated coordinates. Meanwhile, a parameterized selection strategy is proposed first time to evaluate the construction of reference nodes in 3D target tracking. We provide a mathematical proof for our strategy, which avoids the ambiguity occurrence caused by the distribution of reference nodes. The new scheme provided for underwater acoustic tracking (UWAT) greatly improves the positioning accuracy in mixed LOS/NLOS environment. At the end of the paper, simulations are illustrated to evaluate and validate the algorithmic superiority and effectiveness. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the joint uplink power allocation problem for the macrocell and femtocells in the new view of Control Theory. Since the wireless channels in the macrocell and the femtocells fluctuate with time, we aim at an energy-saving and adaptive power allocation scheme that is robust to channel fluctuations. An optimal power allocation problem, which can satisfy the requirement of signal-to-interference-plus-noise ratio and subject to the maximum power constraint, is formulated. To obtain the robust power allocation of each user (both macrocell and femtocell users), a second-order control system is created for each cell (macrocell and femtocell). According to the second-order control system and considering the maximum power constraint, we derive a distributed robust power control algorithm. The dynamic performance and convergence of the formulated system are analyzed based on control theory. The advantage of the scheme is that some dynamic control indexes can be set in advance and the dynamic process can be controlled by setting appropriate parameters. Since femtocells share the same spectrum with the macrocell, the interference from femtocells to the macrocell base station has to be controlled to protect the normal communication of the macrocell. Then an admission control algorithm is proposed to remove the user that causes the serious interference to the macrocell, if the signal-to-interference-plus-noise ratio requirement of the macrocell user can not be satisfied. Two algorithms are particularly attractive, especially in view of practical implementation issues. Numerical simulation results are presented to illustrate the effectiveness and advantages of the proposed algorithms. [ABSTRACT FROM AUTHOR]

A robust power allocation algorithm is proposed in this paper based on robust game theory. Considering that the channel gains are usually changing with the dynamic environment in practice, the uncertainty will cause the estimation errors of channel gains and deteriorate the quality of services of users. A probability threshold method is used to deal with the uncertainty of the channel gains. To jointly consider the maximum utilities of source node and relay node, a seller-buyer game is introduced and it is proved that the game converges to the unique equilibrium point. Besides, a distributed iteration algorithm is proposed to reduce the information overhead. Numerical results show the effectiveness and robustness of the proposed power algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the outage probability in three different relay modes, namely Amplify-and-Forward (AF), Decode-and-Forward (DF), and Hybrid Decode-Amplify-Forward (HDAF). We derive the closed-form outage probability expressions for cooperative communication. Our aim is to ensure the quality of service (QoS) of the primary link while minimizing the outage probability of the cognitive radio user. The cooperation based spectrum access is investigated at the secondary network. The cognitive transmitter will allocate low power if the quality of service is very rigid. Firstly, it is beneficial that the cooperation is obtained at the cognitive user from the surrounding cognitive users to decrease outage probability. Secondly, we select the best relay that can provide the minimal outage probability for cooperation. Finally, we investigate the outage probability under the peak and average interference constraints. The results indicate that the average interference constraints has lower outage probability than the peak interference constraints, due to the power adaptation between the transmitter and relay. The comparison among three cooperation relay modes shows that the HDAF outperforms the AF and DF. At the same time, we can see that the performance gain of the HDAF cooperation is better than the other modes, and a lower outage probability can be acquired as the number of potential relays increases. [ABSTRACT FROM AUTHOR]

In this paper, we consider a two-tier three phases simultaneous wireless information and power transfer (SWIPT)-enabled down-link cooperative non-orthogonal multiple access (NOMA) system. In inner tier, the farther central user decodes the information of the outer users, and then harvests energy from the base station to serve the outer users as a dedicated relay. In the cooperative phase, the nearer outer user is the potential relay to the further one; the users need to decode the information of the other outer user and also harvest energy for information transmission. The expressions of the achievable rate and outage probability of users are derived based on the transmit power allocation and the power splitting for the SWIPT system. A two-stage optimization problem is formulated by a resource allocation strategy, where the problem is constrained by the power allocations, the requirements of successive interference cancelation, and the outage probability. Since the primary problem of the outer optimization problem is non-convex, the problem is solved by the successive convex approximation (SCA). The rate maximization algorithm based on the dual-loop optimization is further developed. The simulation results validate that the proposed resource allocation scheme is capable of satisfying the performance requirements in a cooperative NOMA system, and the results also demonstrate the advantage of the cooperative NOMA system when implementing the SWIPT on the benchmarks of orthogonal multiple access (OMA). [ABSTRACT FROM AUTHOR]