Quality-of-service Aware Resource Allocations Over High-efficient Wireless Networks

Over past several decades, with the rapidly developing of techniques in mobile wireless networks such as channel coding, multiple antennas, power allocation, medium access control protocol, routing protocol, etc, the rate and the efficiency of wireless networks have been greatly increased. Meanwhile, the requirement of the wireless networks shifts from text and picture transmission to video transmission, which requires the researchers to further increase the rate and the efficiency of the wireless networks. On the other hand, to decrease the energy consumption and reduce the environment contamination, we need to increase the power efficiency of the wireless networks. To satisfy the requirement for high spectrum efficiency and/or high power efficiency, a number of high efficient wireless networks have emerged in recent years,such as wireless full-duplex networks, virtual multiple-input multiple-output networks,device-to-device networks, femtocell networks, spectrum and energy efficiency networks, etc.However, when we increase the spectrum efficiency and/or the power efficiency, how to guarantee the quality of service(Qo S) is still an unsolved problem. Since different types of traffics require different Qo S requirements, it is very challenging to provide Qo S provisioning in wireless networks. Due to the highly-varying wireless channels over time, frequency, and space domains, statistical Qo S provisioning, instead of deterministic Qo S guarantees, has become a recognized feature in wireless networks. The most important metric of the statistical Qo S provisioning mechanism is the delay-QoS.Resource allocation is an effective way to increase the spectrum efficiency and/or the power efficiency while providing statistical Qo S provisioning in wireless networks. With the Qo S-driven resource allocation in terms of the delay requirement and channel state information, the spectrum efficiency and/or the power efficiency can be maximized. This dissertation focuses on Qo S-guaranteed wireless full-duplex networks, virtual multiple-input multiple-output networks, and spectrum and energy efficiency networks. How to use the dynamic Qo S-driven power allocation to maximize the spectrum efficiency and/or the power efficiency while taking statistical Qo S provisioning into account is investigated. The main contributions of this dissertation lie in:1. The Qo S-guaranteed wireless full-duplex networks is investigated. We considertwo typical kinds of wireless full-duplex links: the two nodes wireless bidirectional link and the three nodes wireless unidirectional link. For these two links, we propose the Qo S-guaranteed power allocation schemes to maximize the effective capacity of wireless full-duplex networks. In particular,1)For the two nodes wireless bidirectional link:By integrating information theory with the statistical Qo S principle, we build two models – local transmit power related self-interference(LTPRS) model and local transmit power unrelated self-interference(LTPUS) model to analyze the wireless full-duplex transmission. For both of these two models, we derive the optimal power allocation schemes, which aim at maximizing the system throughput subject to the given delay-Qo S constraint, over wireless bidirectional links with full-duplex transmission. The analyses and numerical results verify that our proposed power allocation scheme can efficiently support diverse Qo S requirements over wireless bidirectional links. Our proposed full-duplex Qo S driven power allocation schemes can obtain larger effective capacity compared with the conventional half-duplex transmission over wireless bidirectional links.2)For the three nodes wireless unidirectional link:We introduce a new control parameter, termed cancellation coefficient, to characterize the performance of full duplex relay transmission mode. For both amplitude-and-forward(AF) and decode-and-forward(DF) relay networks, we develop the dynamic hybrid resource allocation policies under full duplex and half duplex transmission modes to maximize the network throughput for the given delay Qo S constraint measured by the Qo S exponent. The numerical results obtained verify that our proposed resource allocation schemes can support diverse Qo S requirements over wireless relay networks under full duplex and half duplex transmission modes. Our analysis indicates that the optimal effective capacity of perfect full duplex transmission mode is not the just twice as much as the optimal effective capacity of half duplex transmission mode.2. The impact of delay-Qo S requirement on the performance of D2 D and cellular communications in underlaying wireless networks is investigated. By enabling two adjacent mobile devices to establish a direct link, device-to-device(D2D)communication can increase the system throughput over underlaying wireless networks, where D2 D and cellular communications coexist to share the sameradio resource. We propose the optimal power allocation schemes with statistical Qo S provisioning for the following two channel modes: 1). co-channel mode based underlaying wireless networks where D2 D devices and cellular devices share the same frequency-time resource; 2). orthogonal-channel mode based underlaying wireless networks where the frequency-time resource is partitioned into two parts for D2 D devices and cellular devices, respectively.Applying our proposed optimal power allocations into D2 D based underlaying wireless networks, we obtain the maximum network throughput subject to a given delay-Qo S constraint for above-mentioned two underlaying wireless network modes, respectively. Also conducted is a set of numerical and simulation results to evaluate our proposed Qo S-driven power allocation schemes under different delay-Qo S requirements.3. The Qo S-guaranteed V-MIMO networks is investigated. To enable multiple mobile users to transmit their signals simultaneously over the same sub-channels,the virtual multiple-input multiple-output(V-MIMO) techniques can exploit the multiple-input multiple-output(MIMO) spectrum efficiency gain. Traditional VMIMO transmission schemes mainly focus on maximizing the throughput of grouped mobile users without taking into account the quality-of-service(Qo S)provisionings. In this paper, we propose the optimal power allocation schemes with statistical Qo S provisionings to maximize the effective capacity of noncollaborative/collaborative V-MIMO wireless networks, respectively. For noncollaborative V-MIMO wireless networks, the mobile users in one V-MIMO group transmit signals independently over the same sub-channels. In the view point of existing mobile users, they solely occupy the sub-channels. Thus, the existing mobile users employ the Qo S-driven single-user power allocation scheme to maximize their effective capacity. By converting the non-collaborative V-MIMO transmission optimization problem into a strictly convex optimization problem,we derive the Qo S-driven power allocation scheme for the newly added mobile users to maximize their effective capacity. For collaborative V-MIMO wireless networks where the mobile users in one group can collaboratively transmit their signals, we derive the Qo S-driven collaborative power allocation schemes for both the existing and the newly added mobile users.4. The Qo S-guaranteed joint spectrum and power efficiency optimization problemis investigated. We propose an efficient framework to jointly optimize effective spectrum efficiency(ESE) and effective power efficiency(EPE) under different statistical Qo S guarantees constraints to support the real-time traffic over wireless networks. In particular, we derive the relationship between ESE and EPE under statistical Qo S provisioning constraint. Based on this relationship, we obtain the mutually beneficial(MB) region and the contention-based(CB) region. In the MB region, we propose a novel strategy to achieve the joint effective spectrum and power efficiencies optimization using the average transmit power control. In the CB region, we propose the wireless-relay-based strategy to jointly optimize the effective capacity and power efficiency. In both MB and CB regions,we develop the dynamic transmit-power control strategy and the MIMO-based strategy to jointly maximize the effective spectrum and power efficiencies.