Catalin Lacatus

Flexible Spectrum and Power Allocation for OFDM Unlicensed Wireless Systems

Future generations of communication systems will benefit from cognitive radio technology, which significantly improves the efficient usage of the finite radio spectrum resource. In this paper we present a wireless unlicensed system that successfully coexists with the licensed systems in the same spectrum range. The proposed unlicensed system determines the level of signals and noise in each frequency band and properly adjusts the spectrum and power allocations subject to rate constraints. It employs orthogonal frequency-division multiplexing (OFDM) modulation and distributes each transmitted bit energy over all the bands using a novel concept of bit spectrum patterns. A distributed optimization problem is formulated as a dynamic selection of spectrum patterns and power allocations that are better suited to the available spectrum range without degrading the licensed system performance. Bit spectrum patterns are designed based on a normalized gradient approach and the transmission powers are minimized for a predefined quality of service (QoS). At the optimal equilibrium point, the receiver that employs a conventional correlation operation with the replica of the transmitted signal will have the same efficiency as the minimum mean-squared error (MMSE) receiver in the presence of noise and licensed systems. Additionally, the proposed approach maximizes the unlicensed system capacity for the optimal spectrum and power allocations. The performance of the proposed algorithm is verified through simulations.

Interference avoidance with incremental power updates for uplink CDMA systems

The paper presents a distributed algorithm for joint codeword and power adaptation in the uplink of a code division multiple access (CDMA) system, in which users sequentially adjust codewords and powers using gradient-based updates to maximize their individual spectral efficiency subject to constraints on the signal-to-interference plus-noise ratios (SINR). Codeword adaptation is based on greedy interference avoidance which decreases the effective interference seen by users, and is followed by incremental power adaptation. The proposed algorithm is analyzed and illustrated with numerical examples obtained from simulations

Feedback Requirements for Greedy Interference Avoidance

Greedy interference avoidance provides distributed algorithms for CDMA codeword optimization. These algorithms are based on the implicit assumption that active users have access to the correlation matrix of the the received signal, which should be made available to users through a feedback channel. As a consequence the performance of greedy interference avoidance algorithms will be limited by the accuracy with which the correlation matrix is fed back to the users. In this paper we present two schemes that may be used for correlation matrix feedback in greedy interference avoidance algorithms, and study their effects on the system performance. Numerical examples obtained from simulations are presented to illustrate the performance of the proposed correlation feedback methods

Spreading Sequence Design for MC-CDMA Systems

The paper presents a new approach of optimal spreading sequence allocation in the uplink of a multi-carrier code division multiple access (MC-CDMA) system. The algorithm is implemented as a distributed optimization problem, where each user will minimize its cost function, by choosing a codeword that suits better to the interference pattern. Tire optimization problem is treated as a constrained problem over a convex set, for which the optimal spreading sequences are designed based on feasible direction approach. For the optimal spreading sequence, the matched filter (MF) receiver has the same performances as a minimum mean squared (MMSE) receiver in the presence of multi-access interference (MAI) and white noise. The proposed algorithm is analyzed and illustrated with numerical examples obtained from simulations.

Reduced complexity crosscorrelation interference mitigation in GPS-enabled collaborative ad-hoc wireless networks - Theory

Localization based services rely on Global Positioning System (GPS) receivers embedded in the network nodes, but the satellite signal availability is often limited in indoors environment. Collaborative network-assisted GPS algorithms addressed this issue by communicating various assistance data between the nodes or transforming open-sky nodes into virtual GPS satellite transmitters (pseudolites). Even though such approach improves the coverage, the crosscorrelation problem surfaces due to masking of relatively weak available satellite signals by stronger pseudolites. This paper proposes reduced complexity algorithms to mitigate such a self-jamming (near/far) effect in ad hoc networks. The idea is based on adaptive modifications of dispreading GPS codes in receiver nodes to minimize interference caused by strong pseudolite signals. An optimization problem is formulated for the minimization of interference using mean squared error (MSE) as a cost function. Then computational optimization is achieved through adaptive implementation and parameterized dimension reduction of the optimization problem.

Reduced Complexity Algorithm for Spreading Sequence Design

This paper describes a novel gradient descent algorithm for the constrained optimization of spreading sequence design in the uplink of CDMA systems that use codeword adaptation. We prove that the proposed algorithm converges to the optimal sequence. In addition, the paper demonstrates the convergence of the parallel distributed optimization which is confirmed by simulations. Parallel optimization ensures faster convergence and thus reduces computational load. The performance of the parallel algorithm is improved as the number of active users increases.

Adaptive Interference Avoidance for Dynamic Wireless Systems

The paper presents an interference avoidance al- gorithm for codeword and power adaptation in the uplink of a Code Division Multiple Access (CDMA) system with variable number of active users. The algorithm tracks changes in the system configuration, and transitions incrementally from one optimal point corresponding to a given number of active users to a new optimal point corresponding to the new number of active users. The transition uses gradient-based adaptive interference avoidance in which users adapt their codewords to optimize their corresponding spectral efficiency subject to constraints on the signal-to-interference plus noise-ratio (SINR). The algorithm is illustrated with numerical examples obtained from simulations. I. INTRODUCTION Interference avoidance has emerged in the literature as a new technique by which transmitters in a wireless communication system are optimized in response to changing patterns of interference to better suit the environment in which they operate. Currently, interference avoidance algorithms are static in the number of users (1), and each time this changes the algorithms must be reiterated in order to determine the socially optimal solution for the new number of users. We note that other related algorithms for codeword adaptation for uplink CDMA systems (2)-(7) have the same characteristic, and are not adaptable to changing numbers of active users in the system. In order to overcome this limitation, recent research (8) proposes using Grassmannian signatures for use in dynamic systems with variable number of users in the system. These are designed to support a maximum number of active users in the system subject to a given interference level, and have the nice property that interference among users does not change when less users are active in the system. As noted in (8) the disadvantage associated with equiangular Grassmannian signatures is that they may not exist for any desired system configuration specified by given number of users and processing gain value. In this paper we present an alternative approach to dealing with variable number of active users in the uplink of a CDMA system, and propose an adaptive algorithm that moves the system incrementally from an optimal configuration with a given number of active users, to a new optimal configuration with a different number of active users. The transition between the two optimal configurations is based on an adaptive inter- ference avoidance procedure: when a change in the system status occurs this translates in a change of the SINR of active users which will employ a greedy gradient-based technique to optimize their corresponding spectral efficiency subject to

Implementation approaches of adaptive algorithms for crosscorrelation effect compensation in weak signal conditions

In this paper we propose reduced complexity adaptive methods for compensating cross-correlation interference in global positioning system (GPS) receivers operating in weak signal conditions. The idea is to use modified codes in GPS receivers which minimize the mean squared error (MSE) during signal tracking process. In addition, complexity reduction constraints are also included such as autocorrelation thresholding, autocorrelation quantization and so-called group-weighting of modified code elements. The new methods improve the robustness of the system in weak signal conditions while the complexity of the implementation can be traded against the performance.

Spectrum Assignment for Flexible Rate Cognitive OFDM Systems

In this paper we present an adaptive algorithm for spectrum assignment applicable for unlicensed systems that share the same spectrum range with licensed systems. To improve the rate flexibility of the unlicensed systems using orthogonal frequency-division multiplexing (OFDM) modulation schemes, we design an algorithm that is implemented as a distributed optimization problem in each transmitted bit. Each bit cost function is minimized by dynamically choosing the bit spectrum pattern that are better suited to the available spectrum range without degrading the licensed system performances. The optimization problem is treated as a constraint problem for which the optimal bit spectrum patterns are designed based on a feasible direction approach. At the optimal equilibrium point, the receiver that employs a conventional correlation operation with the replica of the transmitted signal will have the same efficiency as the minimum mean squared error (MMSE) receiver in the presence of noise and licensed systems.

Game Theoretic Approach to Joint CDMA Codeword and Power Adaptation

In this paper we present a distributed algorithm for joint codeword and power adaptation in the uplink of a Code Division Multiple Access (CDMA) system from the perspective of non-cooperative game theory. We define a new convex cost function based on which each user adjusts its codeword and power to meet a specified Quality of Service (QoS), and investigate existence and uniqueness of a Nash equilibrium point. Using the game-theoretic approach we also propose an algorithm for adjusting codewords and powers in a dynamic context, with variable QoS for active users. The proposed algorithm is illustrated with numerical examples obtained from simulations.