Wenjun Xu

Sub-carrier allocation combined with coordinated multi-point transmission in multi-cell OFDMA system

In this paper, we proposed a heuristic algorithm to investigate the performance of resource allocation combined with coordinated multipoint(CoMP) in multi-cell OFDMA systems. We first develop an analytical model of resource allocation for an arbitrary number of users in the different cells, and formulate it into an optimization problem that is proved to be NP-complete. To reduce the computational complexity, we then design an algorithm consisted of three steps to approximately resolve the optimization problem. Simulation results show that the system with downlink CoMP transmission can obtain better performance than the conventional system, while satisfying the proportional fairness requirement of users. Furthermore, we found that the system performance greatly depends on the parameter α which is used to distinguish between CoMP user and center user.

Simultaneous wireless information and power transfer for cognitive two-way relaying networks

Simultaneous wireless information and power transfer (SWIPT), which processes information and scavenges energy from the same ambient radio frequency signals, has recently drawn significant attention. In addition, the integration of cognitive radio and two-way relay transmission has emerged as a promising approach for improving spectral efficiency. In this paper, we consider a cognitive two-way relaying network, where the SWIPT-enabled-relay helps two secondary nodes exchange information with the energy harvested from the received signals. The rate maximization problem for the relaying network is formulated under the constraint that interference to the primary user resulting from the transmission of the secondary relaying network cannot exceed the threshold. Based on the mathematical analysis of the problem, we propose a suboptimal joint relay selection and power allocation scheme with the Bisection Search method. Numerical simulations confirm the near-optimality of the proposed scheme by comparing with the optimal solution. Specially, the best two-way relay location is also revealed in simulations.

Graph-based spectrum sharing for multiuser OFDM Cognitive Radio Networks

Spectrum sharing in OFDM-based Cognitive Radio Networks (CRN) is investigated by using graph theory. We consider the networks in which a set of secondary links (SLs) make underlay access to support single-hop ad hoc transmission. Spectrum sharing must be carried out in SLs so that no excessive interference is caused to links of the primary network and maximizes the total achievable rates of SLs. We divide the spectrum sharing into two stages: coarse-scale interference mitigation and SINR-based channel mapping. Interference mitigation is done through constructing weighted undirected interference graph and applying k-max cut method. Then we perform channel-cluster mapping, which takes instantaneous channel quality into consider, on the basis of interference mitigation. Low-complexity heuristic algorithms are proposed to effectively solve the problems of each stage. Numerical simulations for various scenarios are executed to show the superior performance of the proposed schemes.

Distributed Cooperative Multicast in Cognitive Multi-Relay Multi-Antenna Systems

In this letter, cooperative multicast in cognitive relay systems is investigated, where multiple multi-antenna relay nodes help forward the transmitted message from different sources to the corresponding destinations. Our objective is to maximize the global transmission rate scaling factor by cooperatively optimizing the forwarding matrix for each relay node. To solve the problem effectively, we first prove that the optimal forwarding matrix at each relay node is the combination of a multi-stream matched-filter receiver and a multi-stream adaptive beamformer, and then demonstrate that the beamformer design problem can be further transformed into the cognitive multi-group multicast beamforming problem. Finally, a bisection-based algorithm is proposed to find the optimal beamforming vector. Compared to the existing cooperative multicast schemes, the proposed scheme can achieve higher transmission rate and provide better protection for primary nodes.

Underlaid-D2D-assisted cooperative multicast based on social networks

In this paper, device-to-device (D2D) communication is integrated into cooperative multicast to elevate the multicast transmission rate from base station to users. To this end, a new optimization problem, aiming to maximize the overall cooperative multicast rate, is formulated with two essential features 1) D2D communication is exploited to accomplish the data forwarding in the second phase of cooperative multicast, which overcomes the performance bottleneck that time resource has to be bisected for original relay forwarding in conventional cooperative multicast. 2) Social tiers are also taken into account for relay user selection, which can be viewed as a kind of incentive mechanism to enable D2D communication. To solve the problem efficiently, a two-step scheme is presented, in which relay user selection by joint leveraging channel gains and social connections, and power allocation by quantum-behaved particle swarm optimization (QPSO), are carried out sequentially. Numerical simulations show that the proposed social network-based D2D-assisted cooperative multicast scheme performs well, and the performance gap between the proposed power allocation algorithm and upper bound could be limited within 5 % when the system is not heavily loaded. The performance gain over traditional cooperative multicast can reach up to 85 %.

Energy-efficient power and sensing/transmission duration optimization with cooperative sensing in cognitive radio networks

This paper investigates an energy-efficient transmission scheme in cognitive radio networks, where primary users (PUs) may reoccupy the spectrum when secondary users (SUs) is transmitting data. We aim to maximize the energy efficiency by jointly optimizing the transmission power, the fusion rule threshold and the sensing/transmission durations. Firstly, it is derived that for a given fusion rule threshold, the objective function is unimodal while only one optimization parameter varies. Furthermore, we provide the corresponding closed-form expressions of the optimal data transmission duration and transmission power. Finally, the globally unimodal property is proven, and hence, the globally optimal point can be easily found with the proposed algorithm based on the alternating direction method (ADM). Numerical simulation results show that our proposed scheme is much better than the existing ones.

Performance analysis and optimization of DRX mechanism in LTE

To extend user equipment (UE) batterys lifetime, discontinuous reception (DRX) mechanism is employed in Long Term Evolution (LTE) system. In this paper, we propose an analytical model which mainly focuses on the inactivity period. Based on the model, a cost function that considers both energy consumption and response delay is presented. Hence, the target to investigate the proper selection of DRX parameters transforms into a cost minimization problem. We solve the problem with specific constraints. Finally, some numerical results are shown to illustrate that optimizing parameters can make performance improved. By comparing these results, the impact of different parameters on performance is studied.

System performance evaluation of distributed antennas based CoMP in LTE-Advanced

In this paper, we have summarized our analysis about distributed antennas based CoMP in LTE-Advanced and evaluated the system spectrum efficiency in three scenarios. From the results, we can see the proposed scheme achieves a higher throughput compared with centralized antennas based system. The location of antennas closed to sector center leads to the optimal system performance. With the change in the number and location of the antennas, the antennas tend to be scattered placement. The method of clustering, algorithm of antennas selection, and multi-antennas per sector, are worthy of further research.

Joint overlay and underlay resource allocation with weighted fairness in OFDM-based cognitive radio systems

In this paper, the problem of hybrid overlay and underlay spectrum access is investigated for OFDM-based cognitive radio CR systems. Both the metrics for system e.g. capacity and users e.g. fairness are integrated into the unified framework of weighted-capacity maximization with the interference constraint in CR systems. For easing the procedure of resource allocation, two criteria, respectively, for subcarrier assignment and power allocation are theoretically derived based on the Karush-Kuhn-Tucker conditions. Under the guidance of the two criteria, max-capacity subcarrier assignment and optimal power allocation are proposed to flexibly distribute spectrum resources to secondary users. In order to reduce the computational complexity further, a suboptimal power allocation algorithm, referred to as cap-limited waterfilling, is also presented by decomposing the interference constraint. Simulation results show that the capacity and fairness performance of the proposed algorithms is considerably better than the conventional ones in references. The proposed suboptimal algorithm with substantially lower complexity approaches to optimal power allocation in the vicinity of only 1% performance gap. Meanwhile, joint access model is greatly beneficial to spectrum efficiency enhancement in CR systems. Copyright

Inter-session inter-layer network coding-based dual distributed control for heterogeneous-service networks

Recent advances in network coding have shown great potential for efficient information transfer. In this paper, exploiting inter-layer and inter-session network coding, we address the distributed control problem in heterogeneous-service networks (HSNs) with booming multi-rate multicast (MRM) and unicast (UC) services. Different from the literatures on inter-layer/inter-session schemes, heterogeneity and fairness among MRM users and between different services are jointly considered. With the Lagrangian and subgradient method, a decentralized rate control algorithm is developed with little coordination among intermediate nodes, in which only local information is needed to achieve rate, congestion, and fairness balance control. Numerical examples are provided to verify the effectiveness and convergence of the proposed algorithm. Furthermore, we demonstrate the performance improvement and implementation advantages of the proposed algorithm compared with the previous solutions considering layered coding for an MRM service or inter-session coding limited for UC services.