Optimal dynamic bandwidth allocation for complex networks

Traffic capacity of one network strongly depends on the link’s bandwidth allocation strategy. In previous bandwidth allocation mechanisms, once one link’s bandwidth is allocated, it will be fixed throughout the overall traffic transmission process. However, the traffic load of every link changes from time to time. In this paper, with finite total bandwidth resource of the network, we propose to dynamically allocate the total bandwidth resource in which each link’s bandwidth is proportional to the queue length of the output buffer of the link per time step. With plenty of data packets in the network, the traffic handling ability of all links of the network achieves full utilization. The theoretical analysis and the extensive simulation results on complex networks are consistent. This work is valuable for network service providers to improve network performance or to do reasonable network design efficiently.     

基于STM32的NAND flash的块分配框架设计

STM32对大容量数据文件存储与管理问题可通过NAND flash来解决;而NAND flash的高效管理需要文件系统参与;NAND flash有特殊的块读写及擦除机制,一般的嵌入式文件系统组织结构并不完全兼容NAND flash;针对NAND flash的特点兼顾STM32的资源承受力要提出新的NAND flash块分配框架,框架通过块分配槽这种数据结构,在不使用块分配表与垃圾表的情况下,实现了NAND flash均衡负载与垃圾块的回收;同时通过节点分配栈与文件节点表的结合来提高STM32对文件的读写速度,空间利用率和系统性能;仿真实验和计算结果表明该块分配框架可有效提高NAND flash块的均衡负载与节省RAM空间。     

Optimization Algorithms for Joint Power and Sub-Channel Allocation for NOMA-Based Maritime Communications

This paper investigates resource optimization schemes in a marine communication scenario based on non-orthogonal multiple access (NOMA). According to the offshore environment of the South China Sea, we first establish a Longley–Rice-based channel model. Then, the weighted achievable rate (WAR) is considered as the optimization objective to weigh the information rate and user fairness effectively. Our work introduces an improved joint power and user allocation scheme (RBPUA) based on a single resource block. Taking RBPUA as a basic module, we propose three joint multi-subchannel power and marine user allocation algorithms. The gradient descent algorithm (GRAD) is used as the reference standard for WAR optimization. The multi-choice knapsack algorithm combined with dynamic programming (MCKP-DP) obtains a WAR optimization result almost equal to that of GRAD. These two NOMA-based solutions are able to improve WAR performance by 7.47% compared with OMA. Due to the high computational complexity of the MCKP-DP, we further propose a DP-based fully polynomial-time approximation algorithm (DP-FPTA). The simulation results show that DP-FPTA can reduce the complexity by 84.3% while achieving an approximate optimized performance of 99.55%. This advantage of realizing the trade-off between performance optimization and complexity meets the requirements of practical low-latency systems.     

Capacitated,balanced, sequential location-allocation problems on chains and trees

This paper considers finite horizon, multiperiod, sequential, minisum location-allocation problems on chain graphs and tree networks. The demand has both deterministic and probabilistic components, and increases dynamically from period to period. The problem is to locate one additionalcapacitated facility in each of thep specified periods, and to determine the service allocations of the facilities, in order to optimally satisfy the demand on the network. In this context, two types of objective criteria or location strategies are addressed. The first is a myopic strategy in which the present period cost is minimized sequentially for each period, and the second is a discounted present worth strategy. For the chain graph, we analyze ap-facility problem under both these criteria, while for the tree graph, we analyze a 3-facility myopic problem, and a 2-facility discounted present worth problem. All these problems are nonconvex, and we specify a finite set of candidate solutions which may be compared in order to determine a global optimal solution.     

Joint power allocation and user assignment for licensed/unlicensed band users in massive MIMO cellular systems

In this paper, we study the joint user assignment and power allocation for the defined utility function (central cell throughput) maximization in massive Multiple Input-Multiple Output (MIMO) cellular system coexistence with Wireless Fidelity (WiFi) network. Firstly, the power allocation of problem is formulated as a convex optimization. Unfortunately, the formulated problem has not a closed-form solution. For solving the mentioned problem, it is converted to three sub-problem based on the number of lemmas that are expressed. Due to two of these problems remain difficult to solve, this two sub-problem are relaxed. The Ellipsoid algorithm is an iterative algorithm that used for solving of the relaxed problems. In the following, joint user assignment and power allocation will be addressed, in which two approaches are proposed for solving. In the first approach, we propose an iterative algorithm that user assignment problem and power allocation problem are solved in each iteration. In the second approach, at first, users are assigned to licensed and unlicensed bands, then for the obtained arrangement, the power allocation problem is solved. The simulation results showed that the proposed algorithms are significantly close to the benchmark methods.     

Deep Q-learning based optimal resource allocation method for energy harvested cognitive radio networks

In this article, we propose a deep Q-learning based algorithm for optimal resource allocation in energy harvested cognitive radio networks (EH-CRN). In EH-CRN, channel resources of primary users (PU) networks are shared with secondary users (SU) and energy harvesting allows nodes of the CRN to acquire energy from the environment for operation sustainability. However, amount of energy harvested from the environment is not fixed and requires dynamic allocation of resources for obtaining optimum network and throughput capacity. In this work, we overcome the limitations of existing Q-learning based resource allocation schemes which are constrained by large state-space systems and have slow convergence. Proposed deep Q-learning based algorithm improves the resource allocation in EH-CRN, while considering quality of service (QoS), energy and interference constraints. Simulation results show that proposed algorithm provide improved convergence and better resource utilization compared to other techniques in literature.     

Optimal power allocation for maximizing the energy efficiency of NOMA enabled full-duplex coordinated direct and relay transmission (CDRT) system with SWIPT

In this paper, we investigate the energy efficiency (EE) performance of non-orthogonal multiple access (NOMA) enabled full-duplex (FD) coordinated direct and relay transmission (CDRT) system (i.e., NOMA-FD-CDRT system). Firstly, we consider a two-user scenario, where the base station (BS) can directly communicate with the near user, while it requires the help of a dedicated FD relay node to communicate with the far user. In the second part, we consider that there are two near users and two far users in the system. To improve the EE, we consider integrating the simultaneous wireless information and power transfer (SWIPT) technique at the FD relay. We formulate an analytical expression for the overall EE of the SWIPT-assisted NOMA-FD-CDRT system. We determine optimal power allocation (OPA) for the downlink users at the BS that maximizes the EE. An iterative algorithm based on Dinkelbach method is proposed to determine the OPA vector. With the help of detailed numerical and simulation investigations, it is demonstrated that the proposed OPA can provide significant enhancement of EE of the considered SWIPT-assisted NOMA-FD-CDRT system.     

A novel power allocation strategy for cooperative PDMA systems

Cooperative communication technology is of great importance for increasing the user reachable rate, further improving throughput and reducing the outage probability of non-orthogonal multiple access (NOMA) systems. This paper mainly studies the power allocation optimization method based on amplify-and-forward (AF) pattern division multiple access (PDMA) to obtain the maximum achievable throughput. We formulate an optimization problem of user power allocation in a downlink PDMA system with cooperative relaying, the exact expressions of system throughput and user outage probability of the AF-PDMA system are derived, and a novel power allocation optimization method based on uniform distribution and restricted constraints is proposed. The effectiveness of the restricted constraints and optimization method is verified by theoretical analysis and simulation. The studies we have performed showed that the proposed scheme with uniform distribution and restricted constraints can be significantly improved in terms of the system throughput in comparison to the case with a genetic algorithm (GA) and fixed power allocation scheme. Concerning the proposed method, the search space is reduced to 1/3 of the original feasible region, and the runtime of the algorithm accounts for only 20% of the GA runtime.     

RF measurements of a C-band cavity beam position monitor

RF cold test of a novel C-band cavity beam position monitor (PBM) to be used in the SDUVFEL Test Facility is described.The test results are presented and some characteristics discussed.The main parameters obtained are in reasonable agreement with the analytical estimations.Effective suppression of the common mode has been demonstrated.The position sensitivity over the test region of±0.5 mm is about -21.58 dB/10 μm for the TM110 mode and is linear in the central region of the BPM cavity.     

Power control based on the Stackelberg game in two-tier femtocell networks

In this paper, the resource allocation strategy is investigated for a spectrum sharing two-tier femtocell networks, in which a central macrocell is underlaid with distributed femtocells. The spectral radius is introduced to address the conditions that any feasible set of users’ signal-to-interference-plus-noise ratio requirements should satisfy in femtocell networks. To develop power allocation scheme with the derived conditions, a Stackelberg game is formulated, which aims at the utility maximization both of the macrocell user and femtocell users. The distributed power control algorithm is given to reduce the cross-tier interference between the macrocell and femtocell with same channel. At last, admission control algorithm is proposed, aiming to exploit the network resource effectively. Numerical results show that the proposed resource allocation schemes are effective in reducing power consumption and more suitable in the densely deployed scenario of the femtocell networks. Meanwhile, it also presents that the distributed power allocation scheme combined with admission control can protect the performance of all active femtocell users in a robust manner.