Slow Adaptive OFDMA Systems Through Chance Constrained Programming

Adaptive OFDMA has recently been recognized as a promising technique for providing high spectral efficiency in future broadband wireless systems. The research over the last decade on adaptive OFDMA systems has focused on adapting the allocation of radio resources, such as subcarriers and power, to the instantaneous channel conditions of all users. However, such "fast" adaptation requires high computational complexity and excessive signaling overhead. This hinders the deployment of adaptive OFDMA systems worldwide. This paper proposes a slow adaptive OFDMA scheme, in which the subcarrier allocation is updated on a much slower timescale than that of the fluctuation of instantaneous channel conditions. Meanwhile, the data rate requirements of individual users are accommodated on the fast timescale with high probability, thereby meeting the requirements except occasional outage. Such an objective has a natural chance constrained programming formulation, which is known to be intractable. To circumvent this difficulty, we formulate safe tractable constraints for the problem based on recent advances in chance constrained programming. We then develop a polynomial-time algorithm for computing an optimal solution to the reformulated problem. Our results show that the proposed slow adaptation scheme drastically reduces both computational cost and control signaling overhead when compared with the conventional fast adaptive OFDMA. Our work can be viewed as an initial attempt to apply the chance constrained programming methodology to wireless system designs. Given that most wireless systems can tolerate an occasional dip in the quality of service, we hope that the proposed methodology will find further applications in wireless communications

Feedback Allocation For OFDMA Systems With Slow Frequency-domain Scheduling

We study the problem of allocating limited feedback resources across multiple users in an orthogonal-frequency-division-multiple-access downlink system with slow frequency-domain scheduling. Many flavors of slow frequency-domain scheduling (e.g., persistent scheduling, semi-persistent scheduling), that adapt user-sub-band assignments on a slower time-scale, are being considered in standards such as 3GPP Long-Term Evolution. In this paper, we develop a feedback allocation algorithm that operates in conjunction with any arbitrary slow frequency-domain scheduler with the goal of improving the throughput of the system. Given a user-sub-band assignment chosen by the scheduler, the feedback allocation algorithm involves solving a weighted sum-rate maximization at each (slow) scheduling instant. We first develop an optimal dynamic-programming-based algorithm to solve the feedback allocation problem with pseudo-polynomial complexity in the number of users and in the total feedback bit budget. We then propose two approximation algorithms with complexity further reduced, for scenarios where the problem exhibits additional structure.Comment: Accepted to IEEE Transactions on Signal Processin

Energy-Efficient Scheduling and Power Allocation in Downlink OFDMA Networks with Base Station Coordination

This paper addresses the problem of energy-efficient resource allocation in the downlink of a cellular OFDMA system. Three definitions of the energy efficiency are considered for system design, accounting for both the radiated and the circuit power. User scheduling and power allocation are optimized across a cluster of coordinated base stations with a constraint on the maximum transmit power (either per subcarrier or per base station). The asymptotic noise-limited regime is discussed as a special case. %The performance of both an isolated and a non-isolated cluster of coordinated base stations is examined in the numerical experiments. Results show that the maximization of the energy efficiency is approximately equivalent to the maximization of the spectral efficiency for small values of the maximum transmit power, while there is a wide range of values of the maximum transmit power for which a moderate reduction of the data rate provides a large saving in terms of dissipated energy. Also, the performance gap among the considered resource allocation strategies reduces as the out-of-cluster interference increases.Comment: to appear on IEEE Transactions on Wireless Communication

IMPLEMENTATION AND PERFORMANCE ANALYSIS OF LONG TERM EVOLUTION USING SOFTWARE DEFINED RADIO

The overwhelming changes in the field of communication brought about need for high data rates, which led to the development of a system known as Long Term Evolution (LTE). LTE made good use of Orthogonal Frequency Division Multiplexing Access (OFDMA) in its downlink and Single Carrier Frequency Division Multiplexing Access (SCFDMA) in its uplink transmission because of their robust performance. These multiple access techniques are the major focus of study in this thesis, with their implementation in the LTE system. GNU Radio is a software Defined Radio (SDR) platform. It comprises of C++ signal processing libraries. For user simplicity, it has graphical user interface (GUI) known as GNU Radio Companion (GRC), to build a signal processing flow graph. GRC translates any specific task flow graph to a python program which calls inbuiltC++ signal processing blocks. By leveraging this feature and existing modules in GRC, OFDMA and SCFDMA is implemented. In this study we made use of existing OFDMA flow graph of GNU Radio to study the behavior of downlink and general performing SCFDMA system was implemented with some modifications of the existing GNU Radio blocks. With the GNU Radio implementation, we tested the working mechanism of both the systems. OFDMA is used in downlink for achieving high spectral efficiency and SCFDMA was introduced in uplink due to its low PAPR feature. These multiple access schemes have to meet the requirement of high throughput with low BER and PAPR, low delays and low complexity. In this thesis we are focused on evaluating these multiple access techniques in terms of BER and PAPR with modulation techniques like QPSK, 16-QAM and 64-QAM. Performance analysis part is performed in MATLAB

A distributionally robust linear receiver design for multi-access space-time block coded MIMO systems

A receiver design problem for multi-access space-time block coded multiple-input multiple-output systems is considered. To hedge the mismatch between the true and the estimated channel state information (CSI), several robust receivers have been developed in the past decades. Among these receivers, the Gaussian robust receiver has been shown to be superior in performance. This receiver is designed based on the assumption that the CSI mismatch has Gaussian distribution. However, in real-world applications, the assumption of Guassianity might not hold. Motivated by this fact, a more general distributionally robust receiver is proposed in this paper, where only the mean and the variance of the CSI mismatch distribution are required in the receiver design. A tractable semi-definite programming (SDP) reformulation of the robust receiver design is developed. To suppress the self-interferences, a more advanced distributionally robust receiver is proposed. A tight convex approximation is given and the corresponding tractable SDP reformulation is developed. Moreover, for the sake of easy implementation, we present a simplified distributionally robust receiver. Simulations results are provided to show the effectiveness of our design by comparing with some existing well-known receivers

Energy-efficient robust resource provisioning in virtualized wireless networks

© 2015 IEEE. This paper proposes a robust resource allocation approach in virtualized wireless networks (VWNs) to address the uncertainty in channel state information (CSI) at the base station (BS) due to estimation error and mobility of users. In this set-up, the resources of an OFDMA-based wireless network are shared among different slices where the minimum reserved rate is considered as the quality-of-service (QoS) requirement of each slice. We formulate the robust resource allocation problem against the worst-case CSI uncertainty, aiming to maximize the overall energy efficiency (EE) of VWN in terms of a newly defined slice utility function. Uncertain CSI is modeled as the sum of its true estimated value and an error assumed to be bounded in a specific uncertainty region. The formulated problem suffers from two major issues: computational complexity and energy-efficiency degradation due to the considered error in the maximum extent. To deal with these issues, we consider a specific form of uncertainty region to solve the robust resource allocation problem via an iterative algorithm. The simulation results demonstrate the effectiveness of the proposed algorithms

Energy-Efficient Resource Allocation for Device-to-Device Underlay Communication

Device-to-device (D2D) communication underlaying cellular networks is expected to bring significant benefits for utilizing resources, improving user throughput and extending battery life of user equipments. However, the allocation of radio and power resources to D2D communication needs elaborate coordination, as D2D communication can cause interference to cellular communication. In this paper, we study joint channel and power allocation to improve the energy efficiency of user equipments. To solve the problem efficiently, we introduce an iterative combinatorial auction algorithm, where the D2D users are considered as bidders that compete for channel resources, and the cellular network is treated as the auctioneer. We also analyze important properties of D2D underlay communication, and present numerical simulations to verify the proposed algorithm.Comment: IEEE Transactions on Wireless Communication

Resource management in QoS-aware wireless cellular networks

2011 Summer.Includes bibliographical references.Emerging broadband wireless networks that support high speed packet data with heterogeneous quality of service (QoS) requirements demand more flexible and efficient use of the scarce spectral resource. Opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multiuser diversity. In this work, we study two types of resource allocation problems in QoS-aware wireless cellular networks. First, we develop a rigorous framework to study opportunistic scheduling in multiuser OFDM systems. We derive optimal opportunistic scheduling policies under three common QoS/fairness constraints for multiuser OFDM systems--temporal fairness, utilitarian fairness, and minimum-performance guarantees. To implement these optimal policies efficiently, we provide a modified Hungarian algorithm and a simple suboptimal algorithm. We then propose a generalized opportunistic scheduling framework that incorporates multiple mixed QoS/fairness constraints, including providing both lower and upper bound constraints. Next, taking input queues and channel memory into consideration, we reformulate the transmission scheduling problem as a new class of Markov decision processes (MDPs) with fairness constraints. We investigate the throughput maximization and the delay minimization problems in this context. We study two categories of fairness constraints, namely temporal fairness and utilitarian fairness. We consider two criteria: infinite horizon expected total discounted reward and expected average reward. We derive and prove explicit dynamic programming equations for the above constrained MDPs, and characterize optimal scheduling policies based on those equations. An attractive feature of our proposed schemes is that they can easily be extended to fit different objective functions and other fairness measures. Although we only focus on uplink scheduling, the scheme is equally applicable to the downlink case. Furthermore, we develop an efficient approximation method--temporal fair rollout--to reduce the computational cost

RESOURCE ALLOCATION FOR WIRELESS RELAY NETWORKS

In this thesis, we propose several resource allocation strategies for relay networks in the context of joint power and bandwidth allocation and relay selection, and joint power allocation and subchannel assignment for orthogonal frequency division multiplexing (OFDM) and orthogonal frequency division multiple access (OFDMA) systems. Sharing the two best ordered relays with equal power between the two users over Rayleigh flat fading channels is proposed to establish full diversity order for both users. Closed form expressions for the outage probability, and bit error probability (BEP) performance measures for both amplify and forward (AF) and decode and forward (DF) cooperative communication schemes are developed for different scenarios. To utilize the full potentials of relay-assisted transmission in multi user systems, we propose a mixed strategy of AF relaying and direct transmission, where the user transmits part of the data using the relay, and the other part is transmitted using the direct link. The resource allocation problem is formulated to maximize the sum rate. A recursive algorithm alternating between power allocation and bandwidth allocation steps is proposed to solve the formulated resource allocation problem. Due to the conflict between limited wireless resources and the fast growing wireless demands, Stackelberg game is proposed to allocate the relay resources (power and bandwidth) between competing users, aiming to maximize the relay benefits from selling its resources. We prove the uniqueness of Stackelberg Nash Equilibrium (SNE) for the proposed game. We develop a distributed algorithm to reach SNE, and investigate the conditions for the stability of the proposed algorithm. We propose low complexity algorithms for AF-OFDMA and DF-OFDMA systems to assign the subcarriers to the users based on high SNR approximation aiming to maximize the weighted sum rate. Auction framework is proposed to devise competition based solutions for the resource allocation of AF-OFDMA aiming tomaximize either vi the sum rate or the fairness index. Two auction algorithms are proposed; sequential and one-shot auctions. In sequential auction, the users evaluate the subcarrier based on the rate marginal contribution. In the one-shot auction, the users evaluate the subcarriers based on an estimate of the Shapley value and bids on all subcarriers at once