Performance Optimization Over Wireless Links With Operating Constraints

Wireless communication is one of the most active areas of technological innovations and groundbreaking research ranging from simple cellular phones to highly complex military monitoring devices. The emergence of radios with cognitive capabilities like software defined radios has revolutionized modern communication systems by providing transceivers which can vary their output waveforms as well as their demodulation methods. This adaptability plays a pivotal role in efficient utilization of radio spectrum in an intelligent way while simultaneously not interfering with other radio devices operating on the same frequency band. Thus, it is safe to say that current and future wireless systems and networks depend on their adaptation capability which in turn presents many new technical challenges in hardware and protocol design, power management, interference metrics, distributed algorithms, Quality of Service (QoS) requirements arid security issues. Transmitter adaptation methods have gained importance, and numerous transmitter optimization algorithms have been proposed in recent years. The main idea behind these algorithms is to optimize the transmitted signals according to the patterns of interference in the operating environment such that some specific criterion is optimized. In this context, the objective of this dissertation is to propose transmitter adaptation algorithms in conjunction with power control for wireless systems focusing on performance optimization based on operating constraints. Specifically, this dissertation achieves joint transmitter adaptation and power control in the uplink and downlink of wireless systems with applications to Multiple-Input-Multiple-Output (MIMO) wireless systems and cognitive radio networks. In addition, performance of the proposed algorithms are evaluated in the context of fading channels, taking into consideration the time-varying nature of wireless channels

On rate capacity and signature sequence adaptation in downlink of MC-CDMA system

This dissertation addresses two topics in the MC-CDMA system: rate capacity and adaptation of users\u27 signature sequences. Both of them are studied for the downlink communication scenario with multi-code scheme. The purpose of studying rate capacity is to understand the potential of applying MC-CDMA technique for high speed wireless data communications. It is shown that, to maintain high speed data transmission with multi-code scheme, each mobile should cooperatively decode its desired user\u27s encoded data symbols which are spread with different signature sequences simultaneously. Higher data rate can be achieved by implementing dirty paper coding (DPC) to cooperatively encode all users\u27 data symbols at the base station. However, the complexity of realizing DPC is prohibitively high. Moreover, it is found that the resource allocation policy has profound impact on the rate capacity that can be maintained in the system. Nevertheless, the widely adopted proportional resource allocation policy is only suitable for the communication scenario in which the disparity of users\u27 channel qualities is small. When the difference between users\u27 channel qualities is large, one must resort to non-proportional assignment of power and signature sequences. Both centralized and distributed schemes are proposed to adapt users\u27 signature sequences in the downlink of MC-CDMA system. With the former, the base station collects complete channel state information and iteratively adapts all users\u27 signature sequences to optimize an overall system performance objective function, e.g. the weighted total mean square error (WTMSE). Since the proposed centralized scheme is designed such that each iteration of signature sequence adaptation decreases the WTMSE which is lower bounded, the convergence of the proposed centralized scheme is guaranteed. With the distributed signature sequence adaptation, each user\u27s signature sequences are independently adapted to optimize the associated user\u27s individual performance objective function with no regard to the performance of other users in the system. Two distributed adaptation schemes are developed. In one scheme, each user adapts its signature sequences under a pre-assigned power constraint which remains unchanged during the process of adaptation. In the other scheme, pricing methodology is applied so that the transmission power at the base station is properly distributed among users when users\u27 signature sequences are adapted. The stability issue of these distributed adaptation schemes is analyzed using game theory frame work. It is proven that there always exists a set of signature sequences at which no user can unilaterally adapt its signature sequences to further improve its individual performance, given the signature sequences chosen by other users in the system

Transmitter Optimization in Multiuser Wireless Systems with Quality of Service Constraints

In this dissertation, transmitter adaptation for optimal resource allocation in wireless communication systems are investigated. First, a multiple access channel model is considered where many transmitters communicate with a single receiver. This scenario is a basic component of a. wireless network in which multiple users simultaneously access the resources of a wireless service provider. Adaptive algorithms for transmitter optimization to meet Quality-of-Service (QoS) requirements in a distributed manner are studied. Second, an interference channel model is considered where multiple interfering transmitter-receiver pairs co-exist such that a given transmitter communicates with its intended receiver in the presence of interference from other transmitters. This scenario models a wireless network in which several wireless service providers share the spectrum to offer their services by using dynamic spectrum access and cognitive radio (CR) technologies. The primary objective of dynamic spectrum access in the CR approach is to enable use of the frequency band dynamically and opportunistically without creating harmful interference to licensed incumbent users. Specifically, CR users are envisioned to be able to provide high bandwidth and efficient utilization of the spectrum via dynamic spectrum access in heterogeneous networks. In this scenario, a distributed method is investigated for combined precoder and power adaptation of CR transmitters for dynamic spectrum sharing in cognitive radio systems. Finally, the effect of limited feedback for transmitter optimization is analyzed where precoder adaptation uses the quantized version of interference information or the predictive vector quantization for incremental updates. The performance of the transmitter adaptation algorithms is also studied in the context of fading channels

Transmitter precoding for multi-antenna multi-user communications

Emerging wireless sensor networks and existing wireless cellular and ad hoc networks motivate the design of low-power receivers. Multi-user interference drastically reduces the energy efficiency of wireless multi-user communications by introducing errors in the bits being detected at the receiver. Interference rejection algorithms and multiple antenna techniques can significantly reduce the bit-error-rate at the receiver. Unfortunately, while interference rejection algorithms burden the receiver with heavy signal processing functionalities, thereby increasing the power consumption at the receiver, the small size of receivers, specifically in sensor networks and in downlink cellular communications, prohibits the use of multiple receive antennas. In a broadcast channel, where a central transmitter is transmitting independent streams to decentralized receivers, it is possible for the transmitter to have a priori knowledge of the interference. Multiple antennas can be used at the transmitter to enhance energy efficiency. In some systems, the transmitter has access to virtually an infinite source of power. A typical example would be the base station transmitter for the downlink of a cellular system. The power consumption at receivers can be reduced if some of the signal processing functionality of the receiver is moved to the transmitter.;In this thesis, we consider a wireless broadcast channel with a transmitter equipped with multiple antennas and having a priori knowledge of interference. Our objective is to minimize the receiver complexity by adding extra signal processing functions to the transmitter. We need to determine the optimal signal that should be transmitted so that interference is completely eliminated, and the benefits that can be obtained by using multiple transmit antennas can be maximized. We investigate the use of linear precoders, linear transformations made on the signal before transmission, for this purpose

Efficient Radio Resource Allocation Schemes and Code Optimizations for High Speed Downlink Packet Access Transmission

An important enhancement on the Wideband Code Division Multiple Access (WCDMA) air interface of the 3G mobile communications, High Speed Downlink Packet Access (HSDPA) standard has been launched to realize higher spectral utilization efficiency. It introduces the features of multicode CDMA transmission and Adaptive Modulation and Coding (AMC) technique, which makes radio resource allocation feasible and essential. This thesis studies channel-aware resource allocation schemes, coupled with fast power adjustment and spreading code optimization techniques, for the HSDPA standard operating over frequency selective channel. A two-group resource allocation scheme is developed in order to achieve a promising balance between performance enhancement and time efficiency. It only requires calculating two parameters to specify the allocations of discrete bit rates and transmitted symbol energies in all channels. The thesis develops the calculation methods of the two parameters for interference-free and interference-present channels, respectively. For the interference-present channels, the performance of two-group allocation can be further enhanced by applying a clustering-based channel removal scheme. In order to make the two-group approach more time-efficient, reduction in matrix inversions in optimum energy calculation is then discussed. When the Minimum Mean Square Error (MMSE) equalizer is applied, optimum energy allocation can be calculated by iterating a set of eigenvalues and eigenvectors. By using the MMSE Successive Interference Cancellation (SIC) receiver, the optimum energies are calculated recursively combined with an optimum channel ordering scheme for enhancement in both system performance and time efficiency. This thesis then studies the signature optimization methods with multipath channel and examines their system performances when combined with different resource allocation methods. Two multipath-aware signature optimization methods are developed by applying iterative optimization techniques, for the system using MMSE equalizer and MMSE precoder respectively. A PAM system using complex signature sequences is also examined for improving resource utilization efficiency, where two receiving schemes are proposed to fully take advantage of PAM features. In addition by applying a short chip sampling window, a Singular Value Decomposition (SVD) based interference-free signature design method is presented