A resource management scheme for multi-user GFDM with adaptive modulation in frequency selective fading channels

The topic is "Low-latency communication for machine-type communication in LTE-A" and need to be specified in more detail.This final project focus on designing and evaluating a resource management scheme for a multi-user generalized frequency division multiplexing (GFDM) system, when a frequency selective fading channel and adaptive modulation is used. GFDM with adaptive subcarrier, sub-symbol and power allocation are considered. Assuming that the transmitter has a perfect knowledge of the instantaneous channel gains for all users, I propose a multi-user GFDM subcarrier, sub-symbol and power allocation algorithm to minimize the total transmit power. This work analyzes the performance of using a specific set of parameters for aligning GFDM with long term evolution (LTE) grid. The results show that the performance of the proposed algorithm using GFDM is closer to the performance of using OFDM and outperforms multiuser GFDM systems with static frequency division multiple access (FDMA) techniques which employ fixed subcarrier allocation schemes. The advantage between GFDM and OFDM is that the latency of the system can be reduced by a factor of 15 if independent demodulation is considered.El objetivo de este proyecto final es el de diseñar y evaluar un esquema para administrar los recursos de un sistema multi-usuario donde se utiliza generalized frequency division multiplexing (GFDM), cuando el canal es de frequencia de desvanecimiento selectivo y se utiliza modulación adaptiva. Consideramos un sistema GFDM con subportadora, sub-símbolo i asignación de potencia adaptiva. Asumiendo que el transmisor conoce perfectamente el estado del canal para todos los usuarios, propongo un algoritmo que asigna los recursos de forma que la potencia total de transmisión es mínima. Este trabajo analiza la eficiencia de utilizar un grupo de parámetros concretos para alinear el sistema GFDM con el sistema de LTE. Los resultados muestran que el comportamiento del algoritmo en GFDM es muy similar al de OFDM, pero mucho mayor que cuando se compara con sistemas de asignación de recursos estáticos.L’objectiu d’aquest projecte final es dissenyar i avaluar un esquema per administrar els recursos per a un sistema multi-usuari fent servir generalized frequency division multiplexing (GFDM), quan el canal es de freqüència esvaniment selectiu i es fa servir modulació adaptativa. Considerem un sistema GFDM amb subportadora, sub-símbol i assignació de potencia adaptativa. Assumint que el transmissor coneix perfectament l’estat del canal per tots els usuaris, proposo un algoritme que assigna els recursos de forma que la potencia total de transmissió es la mínima. Aquest treball analitza l’eficiència de fer servir un grup de paràmetres concrets per tal d’alinear el sistema GFDM amb el sistema de LTE. Els resultats mostren que el comportament de l’algoritme en GFDM es molt similar al de OFDM i que millora bastant els resultats quan el comparem amb sistemes d’assignament de recursos estàtics

Interference-Aware Downlink Resource Management for OFDMA Femtocell Networks

Femtocell is an economical solution to provide high speed indoor communication instead of the conventional macro-cellular networks. Especially, OFDMA femtocell is considered in the next generation cellular network such as 3GPP LTE and mobile WiMAX system. Although the femtocell has great advantages to accommodate indoor users, interference management problem is a critical issue to operate femtocell network. Existing OFDMA resource management algorithms only consider optimizing system-centric metric, and cannot manage the co-channel interference. Moreover, it is hard to cooperate with other femtocells to control the interference, since the self-configurable characteristics of femtocell. This paper proposes a novel interference-aware resource allocation algorithm for OFDMA femtocell networks. The proposed algorithm allocates resources according to a new objective function which reflects the effect of interference, and the heuristic algorithm is also introduced to reduce the complexity of the original problem. The Monte-Carlo simulation is performed to evaluate the performance of the proposed algorithm compared to the existing solutions

Weighted Max-Min Resource Allocation for Frequency Selective Channels

In this paper, we discuss the computation of weighted max-min rate allocation using joint TDM/FDM strategies under a PSD mask constraint. We show that the weighted max-min solution allocates the rates according to a predetermined rate ratio defined by the weights, a fact that is very valuable for telecommunication service providers. Furthermore, we show that the problem can be efficiently solved using linear programming. We also discuss the resource allocation problem in the mixed services scenario where certain users have a required rate, while the others have flexible rate requirements. The solution is relevant to many communication systems that are limited by a power spectral density mask constraint such as WiMax, Wi-Fi and UWB

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

Optimization of resource allocation for the downlink of multiuser MISO-OFDM systems

Proceedings of the IEEE International Conference on Telecommunications, 2010, p. 266-271In this paper, we investigate the optimization problem of resource allocation in downlink of multiuser MISO-OFDM system. Multiple users with different BER and minimum transmission rate requirements are considered. We propose a novel heuristic allocation algorithm (HAA) of radio resource, which minimizes the total transmit power of the base station while meeting individual users'QoS requirements. The proposed algorithm combines antenna selection, subcarrier, bit and power allocation together, pre-estimating number of subcarriers assigned to each user and number of bits loaded for each subcarrier to reduce search number, reducing about 8 dB average bit SNR comparing with fixed allocation algorithm (FAA), and acquiring asymptotic average bit SNR of optimal allocation algorithm (OAA) with much lower complexity. © 2009 IEEE.published_or_final_versio

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing

The enormous success of advanced wireless devices is pushing the demand for higher wireless data rates. Denser spectrum reuse through the deployment of more access points per square mile has the potential to successfully meet the increasing demand for more bandwidth. In theory, the best approach to density increase is via distributed multiuser MIMO, where several access points are connected to a central server and operate as a large distributed multi-antenna access point, ensuring that all transmitted signal power serves the purpose of data transmission, rather than creating "interference." In practice, while enterprise networks offer a natural setup in which distributed MIMO might be possible, there are serious implementation difficulties, the primary one being the need to eliminate phase and timing offsets between the jointly coordinated access points. In this paper we propose AirSync, a novel scheme which provides not only time but also phase synchronization, thus enabling distributed MIMO with full spatial multiplexing gains. AirSync locks the phase of all access points using a common reference broadcasted over the air in conjunction with a Kalman filter which closely tracks the phase drift. We have implemented AirSync as a digital circuit in the FPGA of the WARP radio platform. Our experimental testbed, comprised of two access points and two clients, shows that AirSync is able to achieve phase synchronization within a few degrees, and allows the system to nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC and higher layer aspects of a practical deployment. To the best of our knowledge, AirSync offers the first ever realization of the full multiuser MIMO gain, namely the ability to increase the number of wireless clients linearly with the number of jointly coordinated access points, without reducing the per client rate.Comment: Submitted to Transactions on Networkin