Abstract-In this paper we consider transmit and receive selection methods designed to achieve high channel capacities in a single-user MIMO link. A variety of radio channels are considered, including i.i.d. Rayleigh, correlated Rayleigh and Ricean fading environments. Also considered is the presence of imperfect channel state information (CSI) and a simplified waterfilling scheme. In all cases, we evaluate the performance of optimal selection, simple norm-based selection and other benchmark selection techniques. The major contribution is a general approach to analyzing the capacity of the norm-based selection schemes via a simple power scaling factor. We are able to assess the impact of different channels, imperfect CSI and power allocation using this power scaling factor. Furthermore, the analysis is valid for all scenarios: transmit selection, receive selection and joint transmit-receive selection. Results are shown which compare the capacity performance over a wide range of cases. A notable conclusion is that optimal selection, which is computationally intensive, is outperformed at low signal-to-noiseratios by the simple norm-based approach with power allocation.
Abstract-In this paper we consider transmit and receive selection methods designed to achieve high channel capacities in a single-user MIMO link. A variety of radio channels are considered, including i.i.d. Rayleigh, correlated Rayleigh and Ricean fading environments. Also considered is the presence of imperfect channel state information (CSI) and a simplified waterfilling scheme. In all cases, we evaluate the performance of optimal selection, simple norm based selection and other benchmark selection techniques. The major contribution is a general approach to analyzing the capacity of the selection schemes via a simple power scaling factor. We are able to assess the impact of different channels, imperfect CSI and power allocation using this power scaling factor. Furthermore, the analysis is valid for all scenarios: transmit selection, receive selection and joint transmit-receive selection. Results are shown which compare the capacity performance over a wide range of cases. A notable conclusion is that optimal selection, which is computationally intensive, is outperformed at low SNR by the simple, norm based approach with power allocation.
Abstract-For MIMO broadcast systems the effects of shadowing on the channel capacity and the fairness of the system in sharing the resources amongst multiple users are important issues that need to be addressed. In this paper we consider a variety of capacity-approaching algorithms for MIMO broadcast channels. We compare the performance of these algorithms in terms of their ability to approach the sum-capacity and their fairness in sharing the channel resources amongst the multiple users. We also model distance-based attenuation effects and shadowing, yielding valuable insights into the relative performances of the algorithms under varying SNR conditions. Using a novel approach of mapping the broadcast channel to an "equivalent' single-user channel followed by power scaling, we derive closed-form analytical approximations for the capacity of MIMO broadcast channels. For the more evenly distributed SNR case our approximations are quite accurate, suggesting an analytical lower bound for the well known iterative waterfilling solution. Finally, our Monte Carlo simulations comparing the algorithms point to an inherent tradeoff between sum-capacity and fairness.
Abstract-It is well known that the implementation of multiple-input multiple-output (MIMO) systems in a cellular environment is hampered by the effects of inter-cell interference. In this paper we look at controlling the base station power to increase overall system capacity. We define the optimization problem and show that the sub-optimal solution, where each base station either transmits at maximum power or is switched off, is optimal in the majority of cases. We then develop a simple and practical algorithm to find a near optimal solution. Our results show that simple power control can increase system capacity significantly, especially at high transmit power levels, and with massively reduced complexity with respect to the optimal solution.
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