4 research outputs found
Optimizing Information Freshness in Wireless Networks under General Interference Constraints
Age of information (AoI) is a recently proposed metric for measuring
information freshness. AoI measures the time that elapsed since the last
received update was generated. We consider the problem of minimizing average
and peak AoI in a wireless networks, consisting of a set of source-destination
links, under general interference constraints. When fresh information is always
available for transmission, we show that a stationary scheduling policy is peak
age optimal. We also prove that this policy achieves average age that is within
a factor of two of the optimal average age. In the case where fresh information
is not always available, and packet/information generation rate has to be
controlled along with scheduling links for transmission, we prove an important
separation principle: the optimal scheduling policy can be designed assuming
fresh information, and independently, the packet generation rate control can be
done by ignoring interference. Peak and average AoI for discrete time G/Ber/1
queue is analyzed for the first time, which may be of independent interest
Joint evaluation of channel feedback schemes, rate adaptation, and scheduling in OFDMA downlinks with feedback delays
Orthogonal frequency-division multiple access (OFDMA) systems divide the available bandwidth into orthogonal subchannels and exploit multiuser diversity and frequency selectivity to achieve high spectral efficiencies. However, they require a significant amount of channel state feedback for scheduling and rate adaptation and are sensitive to feedback delays. We develop a comprehensive analysis for OFDMA system throughput in the presence of feedback delays as a function of the feedback scheme, frequency-domain scheduler, and rate adaptation rule. Also derived are expressions for the outage probability, which captures the inability of a subchannel to successfully carry data due to the feedback scheme or feedback delays. Our model encompasses the popular best-n and threshold-based feedback schemes and the greedy, proportional fair, and round-robin schedulers that cover a wide range of throughput versus fairness tradeoff. It helps quantify the different robustness of the schedulers to feedback overhead and delays. Even at low vehicular speeds, it shows that small feedback delays markedly degrade the throughput and increase the outage probability. Further, given the feedback delay, the throughput degradation depends primarily on the feedback overhead and not on the feedback scheme itself. We also show how to optimize the rate adaptation thresholds as a function of feedback delay