Social-sine cosine algorithm-based cross layer resource allocation in wireless network

Cross layer resource allocation in the wireless networks is approached traditionally either by communications networks or information theory. The major issue in networking is the allocation of limited resources from the users of network. In traditional layered network, the resource are allocated at medium access control (MAC) and the network layers uses the communication links in bit pipes for delivering the data at fixed rate with the occasional random errors. Hence, this paper presents the cross-layer resource allocation in wireless network based on the proposed social-sine cosine algorithm (SSCA). The proposed SSCA is designed by integrating social ski driver (SSD) and sine cosine algorithm (SCA). Also, for further refining the resource allocation scheme, the proposed SSCA uses the fitness based on energy and fairness in which max-min, hard-fairness, proportional fairness, mixed-bias and the maximum throughput is considered. Based on energy and fairness, the cross-layer optimization entity makes the decision on resource allocation to mitigate the sum rate of network. The performance of resource allocation based on proposed model is evaluated based on energy, throughput, and the fairness. The developed model achieves the maximal energy of 258213, maximal throughput of 3.703, and the maximal fairness of 0.868, respectively

An Optimization Theoretical Framework for Resource Allocation over Wireless Networks

With the advancement of wireless technologies, wireless networking has become ubiquitous owing to the great demand of pervasive mobile applications. Some fundamental challenges exist for the next generation wireless network design such as time varying nature of wireless channels, co-channel interferences, provisioning of heterogeneous type of services, etc. So how to overcome these difficulties and improve the system performance have become an important research topic. Dynamic resource allocation is a general strategy to control the interferences and enhance the performance of wireless networks. The basic idea behind dynamic resource allocation is to utilize the channel more efficiently by sharing the spectrum and reducing interference through optimizing parameters such as the transmitting power, symbol transmission rate, modulation scheme, coding scheme, bandwidth, etc. Moreover, the network performance can be further improved by introducing diversity, such as multiuser, time, frequency, and space diversity. In addition, cross layer approach for resource allocation can provide advantages such as low overhead, more efficiency, and direct end-to-end QoS provision. The designers for next generation wireless networks face the common problem of how to optimize the system objective under the user Quality of Service (QoS) constraint. There is a need of unified but general optimization framework for resource allocation to allow taking into account a diverse set of objective functions with various QoS requirements, while considering all kinds of diversity and cross layer approach. We propose an optimization theoretical framework for resource allocation and apply these ideas to different network situations such as: 1.Centralized resource allocation with fairness constraint 2.Distributed resource allocation using game theory 3.OFDMA resource allocation 4.Cross layer approach On the whole, we develop a universal view of the whole wireless networks from multiple dimensions: time, frequency, space, user, and layers. We develop some schemes to fully utilize the resources. The success of the proposed research will significantly improve the way how to design and analyze resource allocation over wireless networks. In addition, the cross-layer optimization nature of the problem provides an innovative insight into vertical integration of wireless networks

Cross-layer Congestion Control, Routing and Scheduling Design in Ad Hoc Wireless Networks

This paper considers jointly optimal design of crosslayer congestion control, routing and scheduling for ad hoc wireless networks. We first formulate the rate constraint and scheduling constraint using multicommodity flow variables, and formulate resource allocation in networks with fixed wireless channels (or single-rate wireless devices that can mask channel variations) as a utility maximization problem with these constraints. By dual decomposition, the resource allocation problem naturally decomposes into three subproblems: congestion control, routing and scheduling that interact through congestion price. The global convergence property of this algorithm is proved. We next extend the dual algorithm to handle networks with timevarying channels and adaptive multi-rate devices. The stability of the resulting system is established, and its performance is characterized with respect to an ideal reference system which has the best feasible rate region at link layer. We then generalize the aforementioned results to a general model of queueing network served by a set of interdependent parallel servers with time-varying service capabilities, which models many design problems in communication networks. We show that for a general convex optimization problem where a subset of variables lie in a polytope and the rest in a convex set, the dual-based algorithm remains stable and optimal when the constraint set is modulated by an irreducible finite-state Markov chain. This paper thus presents a step toward a systematic way to carry out cross-layer design in the framework of “layering as optimization decomposition” for time-varying channel models

A Tutorial on Cross-layer Optimization Wireless Network System Using TOPSIS Method

Each other, leading to issues such as interference, limited bandwidth, and varying channel conditions. These challenges require specialized optimization techniques tailored to the wireless environment. In wireless communication networks is to maximize the overall system throughput while ensuring fairness among users and maintaining quality of service requirements. This objective can be achieved through resource allocation optimization, where the available network resources such as bandwidth, power, and time slots are allocated to users in an optimal manner. Optimization-based approaches in wireless resource allocation typically involve formulating the resource allocation problem as an optimization problem with certain constraints.. These techniques provide practical solutions with reduced computational complexity, although they may not guarantee optimality. In summary, optimization-based approaches have been instrumental in studying resource allocation problems in communication networks, including the wireless domain. While techniques from the Internet setting have influenced the understanding of congestion control and protocol design, specific challenges in wireless networks necessitate tailored optimization techniques that account for interference, limited bandwidth, and varying channel conditions. power allocation problem in wireless ad hoc networks Cross-layer optimization refers to the process of jointly optimizing the allocation of resources across different layers of wireless networks, the interactions between different layers become more complex due to the shared medium and time-varying channel conditions.  Nash equilibrium, where no user can unilaterally improve its own performance by changing its strategy. Game theory can capture the distributed nature of wireless networks and provide insights into the behavior of users in resource allocation scenarios Additionally, heuristics and approximation algorithms are often employed in wireless resource allocation due to the complexity of the optimization problems involved. In traditional cellular systems, each user is allocated a fixed time slot for transmission, regardless of their channel conditions. However, in opportunistic scheduling. Alternative parameters for “Data rate Ž kbps, Geographic coverage ,  Service requirements , cost ” Evaluation parameter for “Circuit-switched cell, CDPD, WLAN, Paging, Satellite.” “the first ranking training is obtained with the lowest quality of compensation.

Optimal cross layer design for CDMA-SFBC wireless systems

The demand for high speed reliable wireless services has been rapidly growing. Wireless networks have limited resources while wireless channels suffer from fading, interference and time variations. Furthermore, wireless applications have diverse end to end quality of service (QoS) requirements. The aforementioned challenges require the design of spectrally efficient transmission systems coupled with the collaboration of the different OSI layers i.e. cross layer design. To this end, we propose a code division multiple access (CDMA)-space frequency block coded (SFBC) systems for both uplink and downlink transmissions. The proposed systems exploit code, frequency and spatial diversities to improve reception. Furthermore, we derive closed form expressions for the average bit error rate of the proposed systems. In this thesis, we also propose a cross layer resource allocation algorithm for star CDMA-SFBC wireless networks. The proposed resource allocation algorithm assigns base transceiver stations (BTS), antenna arrays and frequency bands to users based on their locations such that their pair wise channel cross correlation is minimized while each user is assigned channels with maximum coherence time. The cooperation between the medium access control (MAC) and physical layers as applied by the optimized resource allocation algorithm improves the bit error rate of the users and the spectral efficiency of the network. A joint cross layer routing and resource allocation algorithm for multi radio CDMA-SFBC wireless mesh networks is also proposed in this thesis. The proposed cross layer algorithm assigns frequency bands to links to minimize the interference and channel estimation errors experienced by those links. Channel estimation errors are minimized by selecting channels with maximum coherence time. On top, the optimization algorithm routes network traffic such that the average end to end packet delay is minimized while avoiding links with high interference and short coherence time. The cooperation between physical, MAC and network layers as applied by the optimization algorithm provides noticeable improvements in average end to end packet delay and success rat

DYNAMIC RESOURCE ALLOCATION FOR MULTIUSER VIDEO STREAMING

With the advancement of video compression technology and wide deployment of wired/wireless networks, there is an increasing demand of multiuser video communication services. A multiuser video transmission system should consider not only the reconstructed video quality in the individual-user level but also the service objectives among all users on the network level. There are many design challenges to support multiuser video communication services, such as fading channels, limited radio resources of wireless networks, heterogeneity of video content complexity, delay and decoding dependency constraints of video bitstreams, and mixed integer optimization. To overcome these challenges, a general strategy is to dynamically allocate resources according to the changing environments and requirements, so as to improve the overall system performance and ensure quality of service (QoS) for each user. In this dissertation, we address the aforementioned design challenges from a resource-allocation point of view and two aspects of system and algorithm designs, namely, a cross-layer design that jointly optimizes resource utilization from physical layer to application layer, and multiuser diversity that explores the source and channel heterogeneity among different users. We also address the impacts on systems caused by dynamic environment along time domain and consider the time-heterogeneity of video sources and time-varying characteristics of channel conditions. To achieve the desired service objectives, a general resource allocation framework is formulated in terms of constrained optimization problems to dynamically allocate resources and control the quality of multiple video bitstreams. Based on the design methodology of multiuser cross-layer optimization, we propose several systems to efficiently transmit multiple video streams, encoded by current and emerging video codecs, over major types of wireless networks such as 3G cellular system, Wireless Local Area Network, 4G cellular system, and future Wireless Metropolitan Area Networks. Owing to the integer nature of some system parameters, the formulated optimization problems are often integer or mixed integer programming problem and involve high computation to search the optimal solutions. Fast algorithms are proposed to provide real-time services. We demonstrate the advantages of dynamic and joint resource allocation for multiple video sources compared to static strategy. We also show the improvement of exploring diversity on frequency, time, and transmission path, and the benefits from multiuser cross-layer optimization

Cross-Layer Resource Allocation and Scheduling in Wireless Multicarrier Networks

The current dominate layered networking architecture, in which each layer is designed and operated independently, results in inefficient and inflexible resource use in wireless networks due to the nature of the wireless medium, such as time-varying channel fading, mutual interference, and topology variations. In this thesis, we focus on resource allocation and scheduling in wireless orthogonal frequency division multiplexing (OFDM) networks based on joint physical and medium access control (MAC) layer optimization. To achieve orders of magnitude gains in system performance, we use two major mechanisms in resource management: exploiting the time variance and frequency selectivity of wireless channels through adaptive modulation, coding, as well as packet scheduling and regulating resource allocation through network economics. With the help of utility functions that capture the satisfaction level of users for a given resource assignment, we establish a utility optimization framework for resource allocation in OFDM networks, in which the network utility at the level of applications is maximized subject to the current channel conditions and the modulation and coding techniques employed in the network. Although the nonlinear and combinatorial nature of the cross-layer optimization challenges algorithm development, we propose novel efficient dynamic subcarrier assignment (DSA) and adaptive power allocation (APA) algorithms that are proven to achieve the optimal or near-optimal performance with very low complexity. Based on a holistic design principle, we design max-delay-utility (MDU) scheduling, which senses both channel and queue information. The MDU scheduling can simultaneously improve the spectral efficiency and provide right incentives to ensure that all applications can receive their different required quality of service (QoS). To facilitate the cross-layer design, we also deeply investigate the mechanisms of channel-aware scheduling, such as efficiency, fairness, and stability. First, using extreme value theory, we analyze the impact of multiuser diversity on throughput and packet delay. Second, we reveal a generic relationship between a specific convex utility function and a type of fairness. Third, with rigorous proofs, we provide a method to design cross-layer scheduling algorithms that allow the queueing stability region at the network layer to approach the ergodic capacity region at the physical layer.Ph.D.Committee Chair: Ye (Geoffrey) Li; Committee Member: Ian F. Akyildiz; Committee Member: James McClellan; Committee Member: John R. Barry; Committee Member: Xingxing Y

Resource allocation in coordinated multipoint long term evolution-advanced networks

Coordinated Multipoint (CoMP) in Long Term Evolution-Advanced (LTE- Advanced) improves the cell-edge data rates and the network spectral efficiency through base station coordination. In order to achieve high quality of service (QoS) in CoMP network, resource allocation approach is one of the main challenges. The resource allocation strategies of cells in CoMP network affect each other’s performance. Thus, the resource allocation approach should consider various diversities offered in multiuser wireless networks, particularly in frequency, spatial and time dimensions. The primary objective of this research is to develop resource allocation strategy for CoMP network that can provide high QoS. The resource allocation algorithm is developed through three phases, namely Low-Complexity Resource Allocation (LRA), Optimized Resource Allocation (ORA) and Cross-Layer Design of ORA (CLD-ORA). The LRA algorithm is a three-step resource allocation scheme that consists of user selection module, subcarrier allocation module and power allocation module which are performed sequentially in a multi-antenna CoMP network. The proposed ORA algorithm enhances throughput in LRA while ensuring fairness. ORA is formulated based on Lagrangian method and optimized using Particle Swarm Optimization (PSO). The design of CLD-ORA algorithm is an enhancement of the ORA algorithm with resource block (RB) scheduling scheme at medium access control (MAC) layer. Simulation study shows that the ORA algorithm improves the network sum-rate and fairness index up to 70% and 25%, respectively and reduces the average transmit power by 41% in relative to LRA algorithm. The CLD-ORA algorithm has further enhanced the LRA and ORA algorithms with network sum-rate improvement of 77% and 33%, respectively. The proposed resource allocation algorithm has been proven to provide a significant improved performance for CoMP LTE-Advanced network and can be extended to future 5G network

Optimization and Control of Communication Networks

Recently, there has been a surge in research activities that utilize the power of recent developments in nonlinear optimization to tackle a wide scope of work in the analysis and design of communication systems, touching every layer of the layered network architecture, and resulting in both intellectual and practical impacts significantly beyond the earlier frameworks. These research activities are driven by both new demands in the areas of communications and networking, and new tools emerging from optimization theory. Such tools include new developments of powerful theories and highly efficient computational algorithms for nonlinear convex optimization, as well as global solution methods and relaxation techniques for nonconvex optimization. Optimization theory can be used to analyze, interpret, or design a communication system, for both forward-engineering and reverse-engineering. Over the last few years, it has been successfully applied to a wide range of communication systems, from the high speed Internet core to wireless networks, from coding and equalization to broadband access, and from information theory to network topology models. Some of the theoretical advances have also been put into practice and started making visible impacts, including new versions of TCP congestion control, power control and scheduling algorithms in wireless networks, and spectrum management in DSL broadband access networks. Under the theme of optimization and control of communication networks, this Hot Topic Session consists of five invited talks covering a wide range of issues, including protocols, pricing, resource allocation, cross layer design, traffic engineering in the Internet, optical transport networks, and wireless networks