This work proposes a method for the evaluation of the effectiveness of adopting dynamic spectral management (DSM) algorithms in different DSL scenarios. In the last years several DSM algorithms emerged in the literature but their comparison has been typically conducted within few scenarios and considering specific operating points. This work proposes the adoption of the DSM effectiveness factor (DEF) as a figure of merit capable of comparing the volumes of the whole rate regions, which expresses the set of operating points in the Pareto front. A random scenario generator was used to obtain four hundred DSL scenarios and compared flat power backoff (PBO) and DSM algorithms of levels 1 and 2. Besides confirming well-known facts, such that the effectiveness of DSM is significant in near-far scenarios, the results based on the proposed DEF allow to quantify the gains in bit rate that DSM can bring.

Abstract-This paper presents a closed-form upper bound for the ergodic capacity of spatially uncorrelated Ricean flat-fading channels with multiple-input multiple-output (MIMO) antennas. By considering an arbitrary number of antennas at both the transmitter and receiver sides and assuming that the channel state information (CSI) is completely unknown at the transmitter, the Majorization theory is used as a powerful mathematical tool, which allows us to derive an upper bound on the channel capacity for this class of channels. The upper bound obtained does not depend on the Ricean-K factor. Moreover, in the high signal-to-noise-ratio (SNR) regimes, we give another approximation for Ricean-fading channel capacity. Finally, we present some numerical results that illustrate the validity of our approach.

No abstract

No abstract

In this paper, we investigate the ergodic capacity of multiple-input multiple-output (MIMO) wireless communication systems over spatially uncorrelated Rayleigh-fading channels, assuming that the channel state information (CSI) is unknown at the transmitter and perfectly known at the receiver. Applying some results of majorization theory, we provide an analytical closed-form upper-bound to the ergodic capacity at any signalto-noise ratio (SNR). In addition, we also derive an approximation to the ergodic capacity in high-SNR regimes. Finally, we present numerical results that confirm our theoretical analysis.