Yinglei Teng

Reinforcement-Learning-Based Double Auction Design for Dynamic Spectrum Access in Cognitive Radio Networks

In cognitive radio networks, an important issue is to share the detected available spectrum among different secondary users to improve the network performance. Although some work has been done for dynamic spectrum access, the learning capability of cognitive radio networks is largely ignored in the previous work. In this paper, we propose a reinforcement-learning-based double auction algorithm aiming to improve the performance of dynamic spectrum access in cognitive radio networks. The dynamic spectrum access process is modeled as a double auction game. Based on the spectrum access history information, both primary users and secondary users can estimate the impact on their future rewards and then adapt their spectrum access or release strategies effectively to compete for channel opportunities. Simulation results show that the proposed reinforcement-learning-based double auction algorithm can significantly improve secondary users’ performance in terms of packet loss, bidding efficiency and transmission rate or opportunity access.

Dynamic spectrum sharing through double auction mechanism in cognitive radio networks

In this paper, focusing on the spectrum sharing and competition, we propose a double auction based spectrum trading (DAST) scheme which resolves the spectrum access between the primary network (PN) and secondary networks (SNs) subtly. Two different utility functions for primary users (PUs) and secondary users (SUs) are designed basing on a supply-and-demand relationship between them. Also, we adopt expectation and learning process in the module formulation, which takes consideration of the variance of channels, transmission forecasting, afore trading histories and etc. Numerical results with four bidding strategies are presented to reinforce the effectiveness of the two proposed utility evaluation based decision modules in supply falling short of demand cases. Meanwhile, the proposed DAST maintains comparable frequency efficiency with traditional centralized cognitive radio (CR) access approaches.

Genetic algorithm based adaptive resource allocation in OFDMA system for heterogeneous traffic

An adaptive resource allocation scheme for QoS oriented OFDMA system, which schedules two different utility functions for the Real-time/Non Real-time traffic simultaneously, is proposed in this paper. Instead of partial consideration of uniform kinds of QoS, we introduce an updating ratio factor to schedule users of heterogeneous traffic. Due to the complex optimization objective, the general convex optimal methods are no longer feasible. We are motivated to study a heuristic natural genetic approach to solve this problem. Due to the weak convergence of Genetic Algorithm (GA), we improve it by a well-selected initial population. Numerical results are presented to illustrate that our scheme not only tackles the diverse QoS requirement but also alleviates the unfairness between real-time and non-real-time services under various traffic loads.

Performance Analysis of CoMP in Ultra-Dense Networks with Limited Backhaul Capacity

Coordinated multipoint (CoMP) transmission provides an effective way to mitigate inter-cell interference as well as improve network performance in ultra-dense networks (UDNs). However, applying coordination among access points (APs) requires high backhaul capacity (BC), which becomes a bottleneck for employing CoMP. Considering a downlink UDN with limited BC, this paper conducts performance analysis of two CoMP schemes including joint transmission (JT) and coordinated scheduling/beamforming (CS/CB) from three aspects: a typical user’s perspective, a typical AP’s perspective and a network perspective. Firstly, the coverage probability (CP) and ergodic capacity (EC) of a typical user are characterized. Secondly, per-AP backhaul consumption is explicitly quantified and the successful serving probability (SSP) of a typical AP is proposed to capture its robustness to limited BC. Additionally, we propound effective ergodic capacity (EEC) to consider performance gain and backhaul consumption simultaneously from a global perspective. Further, the approximated expressions of all the performance metrics are given so that the impact of cluster size and AP density can be overtly observed. Numerical results illustrate that JT outperforms CS/CB in the case of high BC threshold, small cluster size or high AP density and a comparative smaller size is preferable for both two schemes for practice.

Joint optimization of coverage and capacity in heterogeneous cellular networks

This paper presents a framework for coverage and capacity optimization (CCO) in Heterogeneous Cellular Networks (HCNs). Unlike conventional approaches, we propose a concept of effective capacity (EC) as the optimization objective of CCO, which involves the index of coverage in the form of truncation function. The optimization objective is a NP problem due to that the adjusting parameters are mixed with discrete and continuous, i.e., antenna electronic down-tilt is discrete, while the transmission power and bandwidth are continuous. In this paper, we improve bacterial foraging (BF) algorithm based on taking the HCNs performance analysis of coverage and capacity with percentile level to find an effective increasing direction. According to simulation, the results show that the optimization objective is feasible and the adjustment of percentile level achieves flexible solutions for CCO.

Optimal QoS aware resource allocation for cooperative networks

In this paper, we investigate resource allocation in the OFDMA cooperative networks with Best effort (BE) services and Real time (RT) services. Both Amplify-and-forward (AF) and Decode-and-forward (DF) schemes are considered adaptively in the two-hop relay transmission. We resolve the relay node, relay strategy selection combined subcarrier and power allocation in mixed services resource allocation problem by first satisfying the QoS requirements of RT services with the least power assumption and then maximizing the overall throughput of BE services. Simulation results reveal that our proposed resource allocation method outperforms previous works for mixed services in terms of QoS satisfaction and maintains a relatively high system throughput.

Optimal utility-based QoS aware resource allocation for cooperative networks

We investigate resource allocation in OFDMA cooperative networks with Best effort services and real time services. We design a utility framework to satisfy QoS requirements of different applications. We define network utility as functions of data rate, delay, and packet loss. A utility function is assigned to user-relay pairs or only the user over each subcarrier, and the relay and subcarrier dedicated to achieve the optimal utility will be selected for cooperation transmission. The objective of resource allocation is to strike a balance between maximizing the data rate utility while minimizing the delay and packet loss.

A novel universal authentication protocol based on combined public key in heterogeneous networks

Abstract Based on combined public key (CPK), a novel universal authentication protocol which conforms extensible authentication protocol (EAP) specification in heterogeneous networks was presented, so called EAP-CPK. Subsequently, detailed authentication process and related delay analysis of EAP-CPK in the 3rd Generation Partnership Project wireless local area network (3GPP-WLAN) interworking network were also given. In this paper, parameters from client and server related with mutual authentication process are classified systematically, and detailed verification process by using BurrowsAbadiNeedham89 (BAN) logic analysis is proposed. Security analysis results show that the proposed protocol is secure, and it not only can prevent man-in-the-middle attack and replay attack, but also can make lower system cost.

Fuzzy logic based traffic model considering cross-layer for future cognitive network

Traffic models play an important role in nowadays network, such as engineering, designing and evaluating the network and its performance. But performance predictions from wireless networking laboratory experiments seem to dismatch what is really deployed in future cognitive heterogeneous networks. To generate an appropriate traffic model is one of the major factors hampering researchers ability to make reliable forecasts. This paper proposes a fuzzy logic based traffic model considering cross-layer for cognitive heterogeneous networks. The analyzed traffic is characterized by linkCongestion parameter which is the output of the fuzzy logic control system with the MAC counters: packet error rate to derive linkReliability, and received network layer parameter: latency to determine routing. The advantage of the traffic model using a fuzzy logic approach is that it does not make any statistical assumptions and does not require a huge data sets. It only uses a singleton fuzzifier, min inference and a defuzzifier, all of which are relatively simple and quick to compute. Hence it is fast and secure.

Successful transmission probability analysis for cache-enabled users in mobile networks

Caching popular contents in the storage of users is deemed as an efficient approach to increase energy efficiency, decrease latency, as well as offload backhauls. Due to the mobility feature of use terminals in the real environment, the analysis of successful transmission is particular important in mobile networks. In this paper, the position of cache-enabled users are distributed as a Homogeneous Poisson Point Process (HPPP) and user moves following the random walk mobility (RWM) model. Then, the successful transmission probability is analyzed through the observation of the one step movement of the typical user using stochastic geometry methods. Meanwhile, in order to optimize the successful transmission probability, two methods are considered, i.e., file segmentation transmission (FST) and retransmission mechanism (RM). Simulation results show that the successful transmission probability can be improved by several network parameters, e.g., user density, transmission zone radius and caching probability, but exhibits a decline with increasing velocity or downloading time. Besides, considering segmentation cost, there is a tradeoff for the optimal segment number for the FST and RM schemes.