Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers for WIFI, WIMAX, and Next-Generation Cellular Systems

Burts-by-burst (BbB) adaptive high-speed downlink packet access (HSDPA) style multicarrier systems are reviewed, identifying their most critical design aspects. These systems exhibit numerous attractive features, rendering them eminently eligible for employment in next-generation wireless systems. It is argued that BbB-adaptive or symbol-by-symbol adaptive orthogonal frequency division multiplex (OFDM) modems counteract the near instantaneous channel quality variations and hence attain an increased throughput or robustness in comparison to their fixed-mode counterparts. Although they act quite differently, various diversity techniques, such as Rake receivers and space-time block coding (STBC) are also capable of mitigating the channel quality variations in their effort to reduce the bit error ratio (BER), provided that the individual antenna elements experience independent fading. By contrast, in the presence of correlated fading imposed by shadowing or time-variant multiuser interference, the benefits of space-time coding erode and it is unrealistic to expect that a fixed-mode space-time coded system remains capable of maintaining a near-constant BER

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

SYNCHRONIZATION AND RESOURCE ALLOCATION IN DOWNLINK OFDM SYSTEMS

The next generation (4G) wireless systems are expected to provide universal personal and multimedia communications with seamless connection and very high rate transmissions and without regard to the users’ mobility and location. OFDM technique is recognized as one of the leading candidates to provide the wireless signalling for 4G systems. The major challenges in downlink multiuser OFDM based 4G systems include the wireless channel, the synchronization and radio resource management. Thus algorithms are required to achieve accurate timing and frequency offset estimation and the efficient utilization of radio resources such as subcarrier, bit and power allocation. The objectives of the thesis are of two fields. Firstly, we presented the frequency offset estimation algorithms for OFDM systems. Building our work upon the classic single user OFDM architecture, we proposed two FFT-based frequency offset estimation algorithms with low computational complexity. The computer simulation results and comparisons show that the proposed algorithms provide smaller error variance than previous well-known algorithm. Secondly, we presented the resource allocation algorithms for OFDM systems. Building our work upon the downlink multiuser OFDM architecture, we aimed to minimize the total transmit power by exploiting the system diversity through the management of subcarrier allocation, adaptive modulation and power allocation. Particularly, we focused on the dynamic resource allocation algorithms for multiuser OFDM system and multiuser MIMO-OFDM system. For the multiuser OFDM system, we proposed a lowiv complexity channel gain difference based subcarrier allocation algorithm. For the multiuser MIMO-OFDM system, we proposed a unit-power based subcarrier allocation algorithm. These proposed algorithms are all combined with the optimal bit allocation algorithm to achieve the minimal total transmit power. The numerical results and comparisons with various conventional nonadaptive and adaptive algorithmic approaches are provided to show that the proposed resource allocation algorithms improve the system efficiencies and performance given that the Quality of Service (QoS) for each user is guaranteed. The simulation work of this project is based on hand written codes in the platform of the MATLAB R2007b

Wireless OFDM Systems and Cross-Layer Optimization

The increasing popularity of wireless broadband services nowadays indicates that, future wireless systems will witness a rapid growth of high-data-rate applications with very diverse quality of service requirements. To support such applications under limited radio resources and harsh wireless channel conditions, dynamic resource allocation, which achieves both higher system spectral efficiency and better QoS, has been identified as one of the most promising techniques. In particular, jointly optimizing resource allocation across adjacent and even nonadjacent layers of the protocol stack leads to dramatic improvement in overall system performance. In this article an overview of recent research on dynamic resource allocation, especially for OFDM systems is provided. Recent work and open issues on cross-layer resource allocation and adaptation are also discusse

Space-time-frequency block codes for MIMO-OFDM in next generation wireless systems

In this thesis the use of space-frequency block codes (SFBC) and space-time-frequency block codes (STFBC) in wireless systems are investigated. A variety of SFBC and STFBC schemes are proposed for particular propagation scenarios and system settings where each has its own advantages and disadvantages. The objective is to pro-pose coding strategies with improved flexibility, feasibility and spectral efficiency,and reduce the decoding complexity in an MIMO-OFDM system. Firstly an efficient SFBC with improved system performance is proposed for MIMO-OFDM systems. The proposed SFBC incorporates the concept of matched rotation precoding (MRP) to achieve full transmit diversity and optimal system performance foran arbitrary numberoftransmitantennas,subcarrierinterval andsubcarriergrouping. The MRP is proposed to exploit the inherent rotation and repetition properties of SFBC, arising from the channel power delay profile, in order to fully capture both space and frequency diversity of SFBC in a MIMO-OFDM system. It is able to relax restrictions on subcarrier interval and subcarrier grouping, making it ideal for adaptive/time-varying systems or multiuser systems. The SFBC without an optimization process is unstable in terms of achievable system performance and diversity order, and also risks diversity loss within a specific propagation scenario. Such loss or risk is prominent while wireless propagation channel has a limited number of dominant paths, e.g. relatively close to transmitters or relatively flat topography. Hence in orderto improve the feasibility of SFBC in dynamic scenarios, the lower bound of the coding gain for MRP is derived. The SFBC with MRP is proposed for more practical scenarios when only partial channel power delay profile information is known at the transmit end, for example the wireless channel has dominant propagation paths. The proposed rate one MRP has a relatively simple optimization process that can be transformed into an explicit diagram and hence an optimal result can be derived intuitively without calculations. Next, a multi-rate transmission strategy is proposed for both SFBCand STFBC to balance the system performance and transmission rate. A variety of rate adaptive coding matrices are obtained by a simple truncation of the coding matrix, or by parameter optimization for coding matrices for a given transmission rate and constellation. Pro-posed strategy can easily and gradually adjust the achievable diversity order. As a result it is capable of achieving a relatively smooth balance between system performance and transmission rate in both SFBC and STFBC, without a significant change of coding structure or constellation size. Such tradeoff would be useful to maintain stable Quality of Service (QoS) for users by providing more scalability of achievable performance in a time-varying channel. Finally the decoding procedure of space-time block code (STBC), SFBCand STFBC is discussed. The decoding of all existing STBC/SFBC/STFBC is unified at first, in order to show a concise procedure and make fair comparisons. Then maximum likelihood decoding (MLD) and arbitrary sphere decoding (SD) can be adopted. To reduce the complexity of decoding further, a novel decoding method called compensation de-coding (CD) is presented for a given space-time-frequency coding scheme. By taking advantage of the simplicity of zero-forcing decoding (ZFD) we are able to calculate a compensation vector for the output of ZFD. After modification by utilizing the com-pensation vector, the BER performance can be improved significantly. The decoding procedure is relatively simple and is independent of the constellation size. The per-formance of the proposed decoding method is close to maximum-likelihood decoding for low to medium SNR. A low complexity detection scheme, classifier based decoding (CBD), is further proposed for MIMO systems incorporating spatial multiplexing. The CBD is a hybrid of an equalizer-based technique and an algorithmic search stage. Based on an error matrix and its probability density functions for different classes of error, a particular search region is selected for the algorithmic stage. As the probability of occurrence of error classes with larger search regions is small, overall complexity of the proposed technique remains low, whilst providing a significant improvement in the bit error rate performance

Mathematical optimization techniques for resource allocation and spatial multiplexing in spectrum sharing networks

Due to introduction of smart phones with data intensive multimedia and interactive applications and exponential growth of wireless devices, there is a shortage for useful radio spectrum. Even though the spectrum has become crowded, many spectrum occupancy measurements indicate that most of the allocated spectrum is underutilised. Hence radically new approaches in terms of allocation of wireless resources are required for better utilization of radio spectrum. This has motivated the concept of opportunistic spectrum sharing or the so-called cognitive radio technology that has great potential to improve spectrum utilization. The cognitive radio technology allows an opportunistic user namely the secondary user to access the spectrum of the licensed user (known as primary user) provided that the secondary transmission does not harmfully affect the primary user. This is possible with the introduction of advanced resource allocation techniques together with the use of wireless relays and spatial diversity techniques. In this thesis, various mathematical optimization techniques have been developed for the efficient use of radio spectrum within the context of spectrum sharing networks. In particular, optimal power allocation techniques and centralised and distributed beamforming techniques have been developed. Initially, an optimization technique for subcarrier and power allocation has been proposed for an Orthogonal Frequency Division Multiple Access (OFDMA) based secondary wireless network in the presence of multiple primary users. The solution is based on integer linear programming with multiple interference leakage and transmission power constraints. In order to enhance the spectrum efficiency further, the work has been extended to allow multiple secondary users to occupy the same frequency band under a multiple-input and multiple-output (MIMO) framework. A sum rate maximization technique based on uplink-downlink duality and dirty paper coding has been developed for the MIMO based OFDMA network. The work has also been extended to handle fading scenarios based on maximization of ergodic capacity. The optimization techniques for MIMO network has been extended to a spectrum sharing network with relays. This has the advantage of extending the coverage of the secondary network and assisting the primary network in return for the use of the primary spectrum. Finally, instead of considering interference mitigation, the recently emerged concept of interference alignment has been used for the resource allocation in spectrum sharing networks. The performances of all these new algorithms have been demonstrated using MATLAB based simulation studies