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© 2014 IEEE. Virtual Multiple-Input Multiple-Output (MIMO) is a promising uplink technology that can meet the throughput demand of Long-Term Evolution-Advanced (LTE-A) systems. However, the complexity of scheduling virtual MIMO is a challenge; existing virtual MIMO is therefore limited to best effort applications. We investigate the resource allocation and scheduling problem in a heterogeneous virtual MIMO system where delay sensitive applications are present. The goal is to maximize the system throughput while maintaining delay bound for delay sensitive traffic. To tackle the complexity challenge, we propose two low-complexity suboptimal algorithms, where the key idea is to reduce the search space and iteratively minimize the rate loss respectively. Simulation results show that the rate loss minimization based heuristic algorithm converges to within 99% of the optimal throughput on average and maintains delay bound for delay sensitive users. It also achieves almost the same fairness performance as the optimal solution.

There are a number of clear examples in the instrumental period where positive El Niño events were coincident with a severely weakened summer monsoon over India (ISM). ENSO's influence on the Indian Monsoon has therefore remained the centerpiece of various predictive schemes of ISM rainfall for over a century. The teleconnection between the monsoon and ENSO has undergone a protracted weakening since the late 1980's suggesting the strength of ENSO's influence on the monsoon may vary considerably on multidecadal timescales. The recent weakening has specifically prompted questions as to whether this shift represents a natural mode of climate variability or a fundamental change in ENSO and/or ISM dynamics due to anthropogenic warming. The brevity of empirical observations and large systematic errors in the representation of these two systems in state-of-the-art general circulation models hamper efforts to reliably assess the low frequency nature of this dynamical coupling under varying climate forcings. Here we place the 20th century ENSO-Monsoon relationship in a millennial context by assessing the phase angle between the two systems across the time spectrum using a continuous tree-ring ENSO reconstruction from North America and a speleothem oxygen isotope (δ18O) based reconstruction of the ISM. The results suggest that in the high-frequency domain (≤ 15 yr), El Niño (La Niña) events persistently lead to a weakened (strengthened) monsoon consistent with the observed relationship between the two systems during the instrumental period. However, in the low frequency domain (≥ 60 yr), periods of strong monsoon are, in general, coincident with periods of enhanced ENSO variance. This relationship is opposite to which would be predicted dynamically and leads us to conclude that ENSO is not pacing the prominent multidecadal variability that has characterized the ISM over the last millennium.

Existing mobile video applications are continuously driving up the demand for throughput and better quality of service (QoS) for future Long Term Evolution-Advanced (LTE-A) networks. Multi-User Multiple-Input Multiple-Output (MU-MIMO) is one of the most promising technologies that would meet the throughput demand. Unfortunately, existing MU-MIMO schemes do not consider metrics such as delay, and therefore, cannot meet the QoS requirement of delay sensitive applications, such as mobile video. We propose a new cross-layer MU-MIMO scheduling algorithm, which is referred to as joint channel and delay aware user scheduling (CDAUS), satisfies both the throughput and delay requirements. The key idea of the CDAUS algorithm is to select users to form MU-MIMO based on the delay requirements of individual users, as well as their channel correlations. The priority of the users is carefully designed to leverage their delay and throughput. Simulation results show that the proposed CDAUS algorithm is able to reduce the average delay by up to 30% with a marginal 2% sacrifice of throughput, compared to previous work. It also reduces delay variations and improves fairness among the users. © 2013 IEEE.

The “internally” generated intraseasonal variability of the Indian Summer Monsoon is characterized by intermittent periods of enhanced (“active”) and deficient (“break”) precipitation, which produce a quasi east-west precipitation dipole over the Indian subcontinent. Here we present multicentennial-length and near annually-resolved reconstructions of monsoon precipitation, inferred from absolute-dated and instrumentally calibrated speleothem oxygen isotope records from regions (central and northeast India) that have diametric responses to active-break monsoon circulation patterns. On centennial timescales (AD 1400–2008), precipitation variability from these two regions exhibit opposing behavior, oscillating between periods with a persistently “active-dominated” (AD ∼1700 to 2007) and a “break-dominated” (AD 1400 to ∼1700) regime. The switch between these regimes occurs abruptly (within decades) at a time (AD ∼ 1650–1700) when a proxy record of upwelling intensity from the Arabian Sea suggest an abrupt increase in the monsoon winds. On the basis of these observations, we hypothesize that the frequency distribution of active-break periods varies on centennial timescales, implying a leading role of internal dynamics in governing the ISM response to slowly-evolving changes in the external boundary conditions.

We consider the downlink transmit power allocation problems in multi-user MIMO wireless networks using zeroforcing beamforming. Traditionally such problems are solved by water-filling algorithm under the assumption of perfect channel knowledge. However when channel information is not known a priori or time varying the water-filling solution is shown to be unstable. We use the sliding mode control theory to synthesize the transmit powers so that the target SINR requirements of all users are met. We synthesize the sliding mode controller for the case of zero-forcing beamforming. The synthesis problem is solved under time varying Rayleigh fading channel conditions. Our solutions and simulation results show that our sliding mode controller is stable and delivers better quality of service under practical channel conditions. © 2011 IEEE.