Energy-aware subchannels power allocation for downlink transmissions in OFDMA systems

It is arbitrarily known that the spectrum scarcity issue in the wireless channel has brought to the surface several Quality of Service (QoS)-related challenges for the network operators. Although it is claimed a QoS improvement may be possible if a high wireless signal frequency is generated, this solution does not seem to be compatible with the emerged network scenarios, wherein low power and energy-efficient communications are among the core driving QoS criteria. Minding that, in this paper, we look into the problem of subchannel power allocation at the downlink LTE-A network. Accordingly, an Energy-aware Subchannels Power Allocation (EaSPA) algorithm is proposed to solve the formulated non-convex optimization problem. The system-level simulation experiments imply that the proposed subchannels power allocation model enhances the energy efficiency by 20% compared with a reference scheme. In addition, a low dissipated power level is preserved over different network loads

Partially-Distributed Resource Allocation in Small-Cell Networks

We propose a four-stage hierarchical resource allocation scheme for the downlink of a large-scale small-cell network in the context of orthogonal frequency-division multiple access (OFDMA). Since interference limits the capabilities of such networks, resource allocation and interference management are crucial. However, obtaining the globally optimum resource allocation is exponentially complex and mathematically intractable. Here, we develop a partially decentralized algorithm to obtain an effective solution. The three major advantages of our work are: 1) as opposed to a fixed resource allocation, we consider load demand at each access point (AP) when allocating spectrum; 2) to prevent overloaded APs, our scheme is dynamic in the sense that as the users move from one AP to the other, so do the allocated resources, if necessary, and such considerations generally result in huge computational complexity, which brings us to the third advantage: 3) we tackle complexity by introducing a hierarchical scheme comprising four phases: user association, load estimation, interference management via graph coloring, and scheduling. We provide mathematical analysis for the first three steps modeling the user and AP locations as Poisson point processes. Finally, we provide results of numerical simulations to illustrate the efficacy of our scheme.Comment: Accepted on May 15, 2014 for publication in the IEEE Transactions on Wireless Communication

Investigation of efficient resource allocation schemes for WiMAX networks

This thesis was submitted for the degree of Master of Philosophy and was awarded by Brunel University on 9 July 2008.WiMax (Worldwide Interoperability for Microwave Access) is a promising wireless technology with the aim of providing the last mile wireless broadband access designed for both fixed and mobile consumers as an alternative solution to the wired DSL and cable access schemes. The purpose of this research project is to investigate efficient resource allocation algorithms for WiMax. To achieve this goal, we investigate efficient PHY layer Partial Usage of SubCarriers (PUSC) allocation as well as MAC layer piggyback bandwidth request mechanisms. At the PHY layer we proposed improvements on the Uplink and Downlink PUSC subcarrier allocation scheme. For the Uplink PUSC we suggested a method by allocating different frequencies to neighbouring cells in combination with the Integer Frequency Reuse (IFR) and Fractional Frequency Reuse (FFR) in order to reduce interferences and collisions. The simulation results exhibit that collision rates can be reduced to zero for both IFR and FFR patterns with the proposed improvement by assuming that perfect power control is used in the system. In addition, there is no collision at cell edges. The results also show that FFR patterns achieve lower inter-cell interference and higher capacities as compared to the IFR patterns. For the Downlink PUSC we introduced an offset scheme with the purpose of increasing the number of users in the system. At the MAC layer we propose an improvement on the piggyback bandwidth request mechanism by increasing the size of the piggyback bandwidth request in order to reduce the number of bandwidth requests and hence improve the resource utilisation. The simulation results demonstrate that our improved scheme achieves higher throughput, less delay and packet loss rates as compared to the standardised piggyback bandwidth request mechanism

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

Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining

The deployment of underlay small base stations (SBSs) is expected to significantly boost the spectrum efficiency and the coverage of next-generation cellular networks. However, the coexistence of SBSs underlaid to an existing macro-cellular network faces important challenges, notably in terms of spectrum sharing and interference management. In this paper, we propose a novel game-theoretic model that enables the SBSs to optimize their transmission rates by making decisions on the resource occupation jointly in the frequency and spatial domains. This procedure, known as interference draining, is performed among cooperative SBSs and allows to drastically reduce the interference experienced by both macro- and small cell users. At the macrocell side, we consider a modified water-filling policy for the power allocation that allows each macrocell user (MUE) to focus the transmissions on the degrees of freedom over which the MUE experiences the best channel and interference conditions. This approach not only represents an effective way to decrease the received interference at the MUEs but also grants the SBSs tier additional transmission opportunities and allows for a more agile interference management. Simulation results show that the proposed approach yields significant gains at both macrocell and small cell tiers, in terms of average achievable rate per user, reaching up to 37%, relative to the non-cooperative case, for a network with 150 MUEs and 200 SBSs

Novel Intercell Interference Mitigation Algorithms for Multicell OFDMA Systems with Limited Base Station Cooperation

Resource allocation in multicell downlink orthogonal frequency division multiple-access (OFDMA) systems is investigated, where BSs first independently carry out subcarrier-allocation and then mitigate intercell interference (InterCI) with the aid of very limited base station (BS) cooperation. Two novel InterCI mitigation algorithms are proposed. The first one is the distributed decision making assisted cooperation (DDMC) algorithm, and the second one is the centralized decision making assisted cooperation (CDMC) algorithm. When employing the DDMC algorithm, each BS independently makes the InterCI mitigation decisions. By contrast, when employing the CDMC algorithm, the centralized InterCI mitigation decisions are made with the aid of the cell-edge users’ discrete InterCI information sharing among BSs. While both the algorithms motivate to maximize the spectral-efficiency (sum rate), the CDMC algorithm also aims to maximize the frequency reuse factor. In this paper, we study and compare the performance, including spectral-efficiency of cell-edge users, frequency reuse factor, overhead, etc., of the multicell downlink OFDMA systems employing the proposed and other InterCI mitigation algorithms. Our studies show that both the DDMC and CDMC algorithms can achieve better spectral-efficiency performance than the existing on-off power (OOP) algorithm. Moreover, the CDMC algorithm is capable of achieving the performance close to the upper-bound attained by the so-called full InterCI information assisted decision making (FIIDM) algorithm, which uses exhaustive search to determine the InterCI mitigation decisions. Additionally, the CDMC algorithm is demonstrated to have the highest frequency reuse factor in addition to its spectral-efficiency advantage

Joint relay selection and bandwidth allocation for cooperative relay network

Cooperative communication that exploits multiple relay links offers significant performance improvement in terms of coverage and capacity for mobile data subscribers in hierarchical cellular network. Since cooperative communication utilizes multiple relay links, complexity of the network is increased due to the needs for efficient resource allocation. Besides, usage of multiple relay links leads to Inter- Cell Interference (ICI). The main objective of this thesis is to develop efficient resource allocation scheme minimizes the effect of ICI in cooperative relay network. The work proposed a joint relay selection and bandwidth allocation in cooperative relay network that ensures high achievable data rate with high user satisfaction and low outage percentage. Two types of network models are considered: single cell network and multicell network. Joint Relay Selection and Bandwidth Allocation with Spatial Reuse (JReSBA_SR) and Optimized JReSBA_SR (O_JReSBA_SR) are developed for single cell network. JReSBA_SR considers link quality and user demand for resource allocation, and is equipped with spatial reuse to support higher network load. O_JReSBA_SR is an enhancement of JReSBA_SR with decision strategy based on Markov optimization. In multicell network, JReSBA with Interference Mitigation (JReSBA_IM) and Optimized JReSBA_IM (O_JReSBA_IM) are developed. JReSBA_IM deploys sectored-Fractional Frequency Reuse (sectored- FFR) partitioning concept in order to minimize the effect of ICI between adjacent cells. The performance is evaluated in terms of cell achievable rate, Outage Percentage (OP) and Satisfaction Index (SI). The result for single cell network shows that JReSBA_SR has notably improved the cell achievable rate by 35.0%, with reduced OP by 17.7% compared to non-joint scheme at the expense of slight increase in complexity at Relay Node (RN). O_JReSBA_SR has further improved the cell achievable rate by 13.9% while maintaining the outage performance with reduced complexity compared to JReSBA_SR due to the effect of optimization. The result for multicell network shows that JReSBA_IM enhances the cell achievable rate up to 65.1% and reduces OP by 35.0% as compared to benchmark scheme. Similarly, O_JReSBA_IM has significantly reduced the RN complexity of JReSBA_IM scheme, improved the cell achievable rate up to 9.3% and reduced OP by 1.3%. The proposed joint resource allocation has significantly enhanced the network performance through spatial frequency reuse, efficient, fair and optimized resource allocation. The proposed resource allocation is adaptable to variation of network load and can be used in any multihop cellular network such as Long Term Evolution-Advanced (LTE-A) network