One of the remarkable features of the next generation network is the integration of heterogeneous wireless networks, which enables mobile users with multi-mode terminals access to the best available network seamlessly. However, most of previous work only takes account of either maximizing single user＇s utility or the whole network＇s payoff, rarely considers the negotiation between them. In this paper, we propose a novel network selection approach using improved multiplicative multi-attribute auction （MMA）. At first, an improved MMA method is put forward to define the user＇s utility. Additionally, user cost is defined by considering allocated bandwidth, network load intensity and cost factor parameter. And last the best suitable network is selected according to the user＇s performance-cost-ration. Simulation results confirm that the proposed scheme outperforms the existing scheme in terms of network selection＇s fairness, user＇s performance-cost-ration, load balancing and the number of accommodated users.
This paper presents a novel incremental relaying protocol based on spatial modulation for cooperative transmission over quasi-static rayleigh fading channel, namely spatial modulation incremental relaying （SMIR）, which applies the concept of spatial modulation into incremental relaying. In the proposed protocol, information bits are mapped into two information carrying units： 1） a constellation point in the constellation diagram and 2） the spatial domain, i.e. into the location of a particular cooperative user number. The analytical expression of the frame error rate （FER） for SMIR protocol is derived. Simulation results confirm the presented mathematical analysis and show that SMIR protocol gains 2 and 3 dB in signal to noise ratio （SNR） over the conventional protocol for 3-and 5-bit/symbol transmissions respectively. Moreover, under this protocol the system can achieve a much higher throughput, which means that our proposed protocol brings significant gain in performance.
Cognitive wireless local area network with fibre-connected distributed antennas （CWLAN-FDA） is a promising and efficient architecture that combines radio over fiber, cognitive radio and distributed antenna technologies to provide high speed/high capacity wireless access at a reasonable cost. In this paper, a Q-learning approach is applied to implement dynamic channel assignment （DCA） in CWLAN-FDA. The cognitive access points （CAPs） select and assign the best channels among the industrial, scientific, and medical （ISM） band for data packet transmission, given that the objective is to minimize external interference and acquire better network-wide performance. The Q-learning method avoids solving complex optimization problem while being able to explore the states of a CWLAN-FDA system during normal operations. Simulation results reveal that the proposed strategy is effective in reducing outage probability and improving network throughput.
A cross-layer optimized query routing mismatch alleviation （QRMA） architecture is proposed to mitigate the problem of query routing mismatch （QRM） phenomenon between the structured peer to peer （P2P） overlay and the routing layer in mobile Ad-hoc networks （MANETs）, which is an important issue that results in the inefficiency of lookup process in the system. Explicated with the representative Chord protocol, the proposal exploits the information of topologic neighbors in the routing layer of MANETs to find if there is any optimized alternative next hop in P2P overlay during conventional lookup progress. Once an alternative next hop is detected, it will take the shortcut to accelerate the query procedure and therefore alleviate the QRM problem in scalable MANETs without any assistance of affiliation equipments such as GPS device. The probability of finding out such an alternative node is formulated and the factors that could increase the chance are discussed. The simulation results show that the proposed architecture can effectively alleviate the QRM problem and significantly improve the system performance compared with the conventional mechanism.
A distributed best-relay node selection scheme is investigated for cooperative communications with adaptive modulation and coding （MAC） strategy over underlay-paradigm based cognitive radio （CR） networks. The scheme aims to maximize the average spectral efficiency and meanwhile to guarantee that the primary link is provided with a minimum-rate for a certain percentage of time. Simulation results demonstrate that the proposed scheme can significantly improve the spectral efficiency compared with other existing schemes.
In Cognitive Radio(CR) networks,cooperative communication has been recently regarded as a key technology for improving the spectral utilization efficiency and ensuring the Quality of Service(QoS) for Primary Users(PUs).In this paper,we propose a distributed joint relay selection and power allocation scheme for cooperative secondary transmission,taking both Instantaneous Channel State Information(I-CSI) and residual energy into consideration,where secondary source and destination may have different available spectrum.Specifically,we formulate the cognitive relay network as a restless bandit system,where the channel and energy state transition is characterized by the finite-state Markov chain.The proposed policy has indexability property that dramatically reduces the computation and implementation complexity.Analytical and simulation results demonstrate that our proposed scheme can efficiently enhance overall system reward,while guaranteeing a good tradeoff between achievable date rate and average network lifetime.
In downlink coordinated multi-point（CoMP） system, full cooperation is always not applicable in real world because of its high request in the backhaul. To deal with this problem, clustering decision is made to process transmission. In this paper clustering methods based on the metric signal-to-leakage-plus-noise（SLNR） is proposed. In addition, user scheduling schemes based on SLNR is also put up to make the scheduling set as large as possible. Simulation results show that the proposed clustering methods not only reduce the data sharing among the cooperating base stations（BSs）, but also improve the system throughput compared with the traditional clustering methods based on channel strength.
