Optimizing the correlation properties of spreadingcodes is critical for minimizing inter-channel interference in satellite navigation systems. By improving the codes' correlation sidelobes, we can enhance navigat...
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Optimizing the correlation properties of spreadingcodes is critical for minimizing inter-channel interference in satellite navigation systems. By improving the codes' correlation sidelobes, we can enhance navigation performance while minimizing the required spreadingcode lengths. In the case of low-earth orbit (LEO) satellite navigation, shorter code lengths (on the order of a hundred) are preferred due to their ability to achieve fast signal acquisition. Additionally, the relatively high signal-to-noise ratio in LEO systems reduces the need for longer spreadingcodes to mitigate inter-channel interference. In this work, we propose a two-stage block coordinate descent (BCD) method which optimizes the codes' correlation properties while enforcing the autocorrelation sidelobe zero property. In each iteration of the BCD method, we solve a mixed-integer convex program over a block of 25 binary variables. Our method is applicable to spreadingcode families of arbitrary sizes and lengths, and we demonstrate its effectiveness for a problem with 66 length-127 codes and a problem with 130 length-257 codes.
The aim of this paper is to develop discrete stochastic approximation algorithms that adaptively optimize the spreadingcodes of users in a code-division multiple-access (CDMA) system employing linear minimum mean-squ...
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The aim of this paper is to develop discrete stochastic approximation algorithms that adaptively optimize the spreadingcodes of users in a code-division multiple-access (CDMA) system employing linear minimum mean-square error (MMSE) receivers. The proposed algorithms are able to adapt to slowly time-varying channel conditions. One of the most important properties of the algorithms is their self-learning capability-they spend most of the computational effort at the global optimizer of the objective function. Tracking analysis of the adaptive algorithms is presented together with mean-square convergence. An adaptive-step-size algorithm is also presented for optimally adjusting the step size based on the observations. Numerical examples, illustrating the performance of the algorithms in multipath fading channels, show substantial improvement over heuristic algorithms.
This paper focuses on the cross-layer issue of joint multiuser detection and resource allocation for energy efficiency in wireless code-division multiple-access (CDMA) networks. In particular, assuming that a linear m...
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This paper focuses on the cross-layer issue of joint multiuser detection and resource allocation for energy efficiency in wireless code-division multiple-access (CDMA) networks. In particular, assuming that a linear multiuser detector is adopted in the uplink receiver, the situation considered is that in which each terminal is allowed to vary its transmit power, spreadingcode, and uplink receiver in order to maximize its own utility, which is defined as the ratio of data throughput to transmit power. Applying a game-theoretic formulation, a non-cooperative game for utility maximization is formulated, and it is proved that a unique Nash equilibrium exists, which, under certain conditions, is also Pareto-optimal. Theoretical results concerning the relationship between the problems of signal-to-interference-plus noise ratio (SINR) maximization and mean-square error (MSE) minimization are given, and, by applying the tools of large system analysis, a new distributed power control algorithm is implemented, based on very little prior information about the user of interest. The utility profile achieved by the active users in a large CDMA system is also computed, and, moreover, the centralized socially optimal solution is analyzed. Considerations concerning the extension of the proposed framework to a multi - cell scenario are also briefly detailed. Simulation results confirm that the proposed non-cooperative game largely outperforms competing alternatives, and that it exhibits negligible performance loss with respect to the socially optimal solution, and only in the case in which the number of users exceeds the processing gain. Finally, results also show an excellent agreement between the theoretical closed-form formulas based on large system analysis and the outcome of numerical experiments.
The issue of noncooperative transceiver optimization in the uplink of a multiuser wireless code division multiple access data network with widely linear detection at the receiver is considered. While previous work in ...
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The issue of noncooperative transceiver optimization in the uplink of a multiuser wireless code division multiple access data network with widely linear detection at the receiver is considered. While previous work in this area has focused on a simple real signal model, in this paper, a baseband complex representation of the data is used so as to properly take into account the I and Q components of the received signal. For the case in which the received signal is improper, a widely linear reception structure, processing separately the data and their complex conjugates, is considered. Several noncooperative resource allocation games are considered for this new scenario, and the performance gains granted by the use of widely linear detection are assessed through theoretical analysis. Numerical results confirm the validity of the theoretical findings and show that exploiting the improper nature of the data in noncooperative resource allocation brings remarkable performance improvements in multiuser wireless systems.
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