High-speed train communication system is a typical high-mobility wireless communication network. Resource allocation problem has a great impact on the system performance. However, conventional resource allocation approaches in cellular network cannot be directly applied to this kind of special communication environment. A multidomain resource allocation strategy was proposed in the orthogonal frequency-division multiple access(OFDMA) of high-speed. By analyzing the effect of Doppler shift, sub-channels, antennas, time slots and power were jointly considered to maximize the energy efficiency under the constraint of total transmission power. For the purpose of reducing the computational complexity, noisy chaotic neural network algorithm was used to solve the above optimization problem. Simulation results showed that the proposed resource allocation method had a better performance than the traditional strategy.
In this paper,a utility-based feedback delay-aware and buffer status-aware( FABA) scheduling scheme is proposed for downlink multiuser multiple-input multiple-output orthogonal frequency-division multiple-access( MIMO-OFDMA) systems. The FABA scheme allocates subcarriers to multiusers with an objective of not only maximizing the total system capacity but reducing the system packet loss rate as well. We design a utility function which consists of a feedback estimate module,a proportional fairness module and a buffer monitoring module. The feedback estimate module is used to improve the system throughput by utilizing the Automatic Repeat-reQuest( ARQ) feedback information to combat the fast time-varying fading condition. The proportional fairness module can guarantee the scheduling fairness among users,and the buffer monitoring module can utilize the transmitting buffer status information to avoid high packet loss rate of the system caused by the system congestion. The FABA scheme then formulates the scheduling problem into a problem of overall system utility maximization. We solve the problem by using a heuristic algorithm with low computational complexity. The simulation results show that the proposed FABA scheme outperforms the existing algorithms in terms of the system throughput and the packet loss rate and can also guarantee the fairness demand among users.
Financial and environment considerations present new trends in wireless network known as green communication. As one of the most promising network architectures, the device-to-device （D2D） communication should take seriously account to the energy-efficiency. Most of the existing work in the area of D2D communication only focus on the direct communication, however, the direct link D2D communication has to be limited in practice because of long distance, poor propagation medium and cellular interference, etc. A new energy-efficient multi-hop routing algorithm was investigated for multi-hop D2D system by jointly optimizing channel reusing and power allocation. Firstly, the energy-efficient multi-hop routing problem was formulated as a combinatorial optimization problem. Secondly, to obtain a desirable solution with reasonable computation cost, a heuristic multi-hop routing algorithm was presented to solve the formulated problem and to achieve a satisfactory energy-efficiency performance. Simulation shows the effectiveness of the proposed routing algorithm.
Due to the constraint of single carrier frequency division multiple access （SC-FDMA） adopted in long term evolution （LTE） uplink, subcarriers allocated to single user equipment （UE） must be contiguous. This contiguous allocation constraint limits resource allocation flexibility and makes the resource scheduling problem more complex. Most of the existing work cannot well meet UE＇s quality of service （QoS） requirement, because they just try to improve system performance mainly based on channel condition or buffer size. This paper proposes a novel resource scheduling scheme considering channel condition, buffer size and packet delay when allocating frequency resource. Firstly, optimization function is formulated, which aims to minimize sum of weight for bits still left in UE buffer after each scheduling slot. QoS is the main concern factor here. Then, to get packet delay information, this paper proposes a delay estimation algorithm. Relay node （RN） is introduced to improve overall channel condition. Specific RN selection strategy is also depicted in the scheme. Most important of all, a creative negotiation mechanism is included in the subcarrier allocation process. It can improve the overall system throughput performance in guarantee of user＇s QoS requirement. Simulation results demonstrate that the scheme can greatly enhance system performance like delay, throughput and jitter.
This paper deals with network selection problem for users in heterogeneous network environment. The main context is to improve the TOPSIS( Technique for Order Preference by Similarity to Ideal Solution) network scheme by combining the network properties and the users' requirement accurately and decrease ping-pong effect. The method of entropy and FAHP( Fuzzy Analytic Hierarchy Process) are used to calculate weight value and the sojourn time calculation is used to avoid ping-pang effect. The simulation results show that the improved scheme enhances the more accuracy of network selection than the existing methods and reduces the number of ping-pang effect.
The orthogonal frequency division multiple access( OFDMA) based communication system has been considered as the main trend of next-Generation communication system. But the existing resource allocation algorithm designed for such system is always with high complexity thus hard to be realized. To solve such problem with the constraints of spectrum efficiency and buffer state,a novel cross-layer resource allocation algorithm( RAA) is proposed in this paper. The goal of our RAA is to maximize the system throughput while satisfying several practical constraints,such as fairness among services,head of line( Ho L) delay and diverse quality of service( Qo S) requirements. Due to these constraints,finding the optimal solution becomes a NPhard problem. Therefore in this paper a novel method to solve such problem with acceptable complexity is proposed within following steps: firstly,based on the link state we formulate the ideal subchannel allocation strategy as a convex optimization problem,which can be efficiently solved by our proposed lagrange multiplier technique subchannel allocation( LMTSA) algorithm; secondly,according to the obtained channel allocation matrix,a power allocation algorithm based on the water-filling power allocation( WPA) idea is deployed to get the optimal power allocation matrix combining with adaptive modulation and coding( AMC); finally,through a greedy algorithm,the ultimate subchannel and power allocation matrix can be obtained based on iterative method. The simulation results illustrate that we can achieve the higher throughput and better Qo S performance than the widely-used maximum throughput( MT) algorithm and round robin( RR) algorithm.
As an effective solution for indoor coverage and service offioading from the conventional cellular networks, femtocells have attracted a lot of attention in recent years. This study investigates the resource block （RB） and power allocation in heterogeneous networks （HetNets）. Specifically, the concern here is to maximize the signal to interference-plus-noise ratio （SINR） of macrocell and energy efficiency of femtocell while providing the finite interference. In this paper, the system model is divided to two layers, in which the macro base station and clusters constitute the first layer network; femtocells in cluster make up the second layer network. Because of the different model structures, different game theories are used in different layers. Stackelberg game is used in the first layer, and non-cooperation game is used in the second layer. Meanwhile RB and power levels stand for the actions that are associated with each player in the game. The problem of resource allocation is formulated as a mixed integer programming problem. In order to minimize the complexity of the proposed algorithm, the resource allocation task is decomposed into two sub problems： a RB allocation and a power allocation. The result is compared with the traditional methods, the analysis illustrates the proposed algorithm has a better performance regarding SINR and energy efficiency of the heterogeneous networks.
