CTN Issue: April 2013

1. Interference Shaping for Improved Quality of Experience for Real-Time Video Streaming

Notice: This paper has been recommended as a "Distinguished Paper" in the IEEE ComSoc MMTC Reviewer Letter in April 2013.

The rate at which data can be sent over a wireless link is inherently variable because of the variable link conditions. This variability can be further aggravated by bursty co-channel interference. Low power access points (APs) like femtocells can be a major source of bursty interference, as they are sporadically active due to fewer users served by them. Increasing the number of such APs can lead to further variations in throughput across the network. These throughput variations lead to large quality variations specifically for real-time video, in which case the throughput variations cannot be smoothed out through halting playback and buffering, resulting in a degraded quality of experience (QoE) for the user.

In this paper, the authors propose and analyze a network-level resource management algorithm called interference shaping to smooth out these throughput variations, and hence improve the QoE of video users by reducing the variability of interference. Interference shaping operates by decreasing the transmission power, and hence peak rate, of co-channel APs serving bursty data (best-effort) users. This smooths their transmit power profile and hence the interference caused by them to the video user link, at the cost of a modest rate decrease for best-effort users. The proposed technique is analyzed by mapping the throughput variations for video users to the corresponding video quality fluctuations and packet loss rate. For video users, QoE is quantified by bench-marking against a metric, which incorporates the strong dependence of the current QoE (which is subjective) on the recent past. The QoE of data users is evaluated using a framework, which quantifies the response of human sensory system to an external stimulus.

The proposed technique increases mean video QoE and reduces the QoE variability over time, with a net perceptual increase of about 2-3x in illustrative settings, while incurring insignificant decrease in the QoE for co-channel data users. The presented algorithm introduces a trade-off between the QoE of video users and other data users, and an optimal operating regime depends on the context. A load-aware cellular model with randomly located interfering APs transmitting bursty data is also developed. Using this model, it is shown that aside from smoothing the throughput of the video link, interference shaping may also increase the mean capacity in scenarios where each interfering AP serves a small number of data users. Increased capacity allows a higher video encoding rate and hence results in higher mean quality. Interference shaping can be applied to both unicast and multicast real-time video streaming with gains proportional to the number of video users sharing the same broadcast and interferers in the latter.

Title and author(s) of the original paper in IEEE Xplore:
Title: Interference Shaping for Improved Quality of Experience for Real-Time Video Streaming
Author: Singh, Sarabjot, Jeffrey G. Andrews, and Gustavo de Veciana
This paper appears in: IEEE Journal on Selected Areas in Communications
Issue Date: August 2012

2. Eigenvalue Based Spectrum Sensing Algorithms for Cognitive Radio

Cognitive radio, a solution for resolving spectrum scarcity problem encountered in many countries, has been regarded as one of the most promising technologies for future wireless communications. The critical requirement in cognitive radio design is to ensure that the primary users are well-protected. One way to do so is called spectrum sensing. Due to various practical constraints such as noise power uncertainty, conventional sensing methods are difficult to achieve satisfied detection performance in low signal-to-noise ratio (SNR) environment. This paper discovers how the spatial- and time-domain correlations of the received signals can be utilized for spectrum sensing design. Observing that the correlation matrix of the received signals changes from an identity matrix to a non-identity matrix when the primary signal becomes active, the authors make use of the eigenvalues of the correlation matrix to perceive the existence of the primary signals. The proposed sensing schemes are able to combat the noise power uncertainty issue, and can achieve good performance in low SNR environment. Furthermore, it builds up an interesting bridge between spectrum sensing and the random matrix theory, from which the sensing performance can be quantified with accurate closed-form expressions.

The methods proposed in this paper have been adopted in IEEE 802.22, the first international standard based on cognitive radio technology. The paper is the winner of the first IEEE Communications Society Asia Pacific Board best paper award.

Title and author(s) of the original paper in IEEE Xplore:
Title: Eigenvalue Based Spectrum Sensing Algorithms for Cognitive Radio
Author: Yonghong Zeng and Ying-Chang Liang
This paper appears in: IEEE Transactions on Communications
Issue Date: June 2009

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