Spectrum Leasing as an Incentive towards Uplink Macrocell and Femtocell Cooperation

The concept of femtocell access points underlaying existing communication infrastructure has recently emerged as a key technology that can significantly improve the coverage and performance of next-generation wireless networks. In this paper, we propose a framework for macrocell-femtocell cooperation under a closed access policy, in which a femtocell user may act as a relay for macrocell users. In return, each cooperative macrocell user grants the femtocell user a fraction of its superframe. We formulate a coalitional game with macrocell and femtocell users being the players, which can take individual and distributed decisions on whether to cooperate or not, while maximizing a utility function that captures the cooperative gains, in terms of throughput and delay.We show that the network can selforganize into a partition composed of disjoint coalitions which constitutes the recursive core of the game representing a key solution concept for coalition formation games in partition form. Simulation results show that the proposed coalition formation algorithm yields significant gains in terms of average rate per macrocell user, reaching up to 239%, relative to the non-cooperative case. Moreover, the proposed approach shows an improvement in terms of femtocell users' rate of up to 21% when compared to the traditional closed access policy.Comment: 29 pages, 11 figures, accepted at the IEEE JSAC on Femtocell Network

Toward optimal resource scheduling for Internet of Things under imperfect CSI

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordThe Internet of Things (IoT) increases the numberof connected devices and supports ever-growing complexity of applications. Owing to the constrained physical size, the IoT devices can significantly enhance computation capacity by offloading computation-intensive tasks to the resource-rich edge servers deployed at the base station (BS) via wireless networks. However, how to achieve optimal resource scheduling remains a challenge due to stochastic task arrivals, time-varying wireless channels and imperfect estimation of channel state information (CSI). In this paper, by virtue of the Lyapunov optimization technique, we propose the toward optimal resource scheduling algorithm under imperfect CSI (TORS) to optimize resource scheduling in an IoT environment. A convex transmit power and subchannel allocation problem in TORS is formulated. This problem is then solved via the Lagrangian dual decomposition method. We derive analytical bounds for the time-averaged system throughput and queue backlog. We show that TORS can arbitrarily approach the optimal system throughput by simply tuning an introduced control parameter β without prior knowledge of stochastic task arrivals and the CSI of wireless channels. Extensive simulation results confirm the theoretical analysis on the performance of TORS.National Key Researchand Development ProgramNational Natural Science Foundation of Chin

Resource Management in Next Generation Cellular Networks

Fifth generation of cellular networks brings new challenges to the network operators as new applications create new demands. In this thesis, we will study different topics on cellular networks, explain the challenges of each topic, and propose solutions to tackle these challenges. The topics we consider are: i) uplink scheduling in multi-cell OFDMA networks, ii) downlink scheduling in multi-cell OFDMA networks, iii) full-duplex communications in cellular networks, and iv) cellular networks with intra-cellular traffic. We begin our study with uplink scheduling in 5G networks as its importance has increased in recent years and the related literature is relatively scarce. Scheduling on the uplink is a challenging task mostly due to power and interference management. In practical scenarios, each cell schedules its own users independently from the other cells. In this case, the interference that is received from the neighboring cells cannot be known since the schedules of the other cells are not known. Therefore, interference has to be estimated in order to estimate the rate of each user. When this estimation is not done properly, it can cause resource losses or under-utilization as we show in this thesis. To avoid this problem, all the cells could be scheduled simultaneously using a cloud radio access network (C-RAN) and hence we can take the exact interference into account while scheduling. Formulating the optimal multi-cell scheduler is straightforward, but it is a very large integer problem that cannot be solved easily and fast. We transform it into a more tractable upper bounding problem and solve it with an iterative algorithm. However, it is still not fast enough to be used in real time. Hence, we focus on improving the existing uplink schedulers by proposing practical solutions for the case when there is no C-RAN and for the case when a C-RAN is present. We also propose a soft frequency reuse (SFR) based scheduler that performs much better than the existing schedulers. We then perform a similar study for downlink scheduling that carries the majority of the cellular traffic today. While downlink scheduling is easier than the uplink due to simpler interference management, it is still not trivial to achieve performance comparable to the maximum achievable performance using a practical scheduler. The main contribution of this study is to show that a well-tuned SFR-based local scheduler can perform almost as well as the centralized scheduler and hence a centralized scheme for downlink might not be necessary. We next consider a cellular network where full-duplex communications (FDC) are enabled at the base stations. The coexistence of uplink and downlink transmissions in co-channel cells create new sources of interference that have to be taken into account when studying the performance of FDC. When doing so, traffic asymmetry (TA), i.e., the fact that the traffic is in general much larger on the downlink than on the uplink, should also be considered. We will show that ignoring TA biases the results in favor of FDC. We compute the performance gain that an FDC-enabled multi-cell OFDMA network has over a regular time division duplex (TDD) system considering all sources of interference and TA by formulating a multi-cell centralized scheduling problem. We use it to analyze the impact of each new source of interference as well as of TA. Our conclusion is that, FDC does not improve performance enough in a multi-cell system to warrant its added complexity in an urban setting when TA and the interference have realistic values. The verdict is slightly better in a rural setting. Furthermore, we show that heterogeneous networks can be a better choice than the homogeneous networks to deploy FDC when it is adjusted well. We finalize our study with device-to-device (D2D) communications. With the advent of smart phones, there are many new applications that create local (intra-cellular) traffic among the users in the same network. Most work in the literature focuses on the possibility to utilize a direct link between those users to by-pass the base station. Such transmissions are called D2D mode. However, implementing D2D is not easy due to difficult interference management and not knowing the required channel gains. We face a major problem while studying D2D. We need a clear benchmark to evaluate the performance of D2D mode. To this end, we focus on designing a type-aware scheduler (a scheduler that has the information on the type of traffic, which can be downlink, uplink, or intra-cellular) in a case where direct communication between users is not enabled. This scheduler can be seen as the benchmark against D2D mode. We show that performance gain can be obtained by jointly scheduling the uplink and downlink with respect to the case where the scheduler is blind to the types. We show for a homogeneous network that when the traffic types are known to a scheduler, a significant performance gain can be achieved compared to the case where the traffic types are not known. We also analyze heterogeneous networks that consist of macro cells and small cells and show that large performance gain can be obtained by performing type-aware user association jointly with user scheduling. The main contributions of the thesis are i) to analyze the performance of existing schedulers and see if they perform well enough compared to the maximum achievable performance both on the uplink and the downlink, ii) to propose enhancements or new schedulers when the existing schedulers do not perform well enough, iii) to illustrate when FDC deployment can be useful under which scenarios, and iv) to show the importance of information of traffic types when users with different types of traffic exist

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

Device-to-Device Communication in 5G: Towards Efficient Scheduling

5G wireless networks are expected to carry large traffic volumes due to the growth of mobile devices and the increasing demand for high data rates from applications. Device to device communication is one of the suggested technologies to support this increasing load and enhance the capacity of networks. However, the implementation of D2D communication reveals many barriers that include communication scheduling, for which the architecture remains complex and obscure. In this paper, an overview of the available literature on the implementation of networks supporting D2D communication is presented, emphasizing the complexity of the offered solutions. This paper also offers a study of the impact of different device distribution models on the throughput of the devices. The paper introduces the challenges and makes the case for the need to find a more efficient D2D scheduler providing less complexity