Achieving Maximum Effective Capacity in OFDMA Networks Operating Under Statistical Delay Guarantee

Abstract

We propose a spectrally efficient design that guarantees the statistical delay quality-ofservice (QoS) for delay-sensitive traffic in the downlink of orthogonal frequency-division multiple-access (OFDMA) networks. This design is based on the so-called effective capacity (EC) concept, which describes the maximum throughput, a system can achieve under a specific statistical delay-QoS violation probability constraint. We investigate the EC maximization problem, in which, the statistical delay profile of the traffic is characterized by the QoS-exponent θ determining the exponential decay rate of the delay-QoS violation probability. By exploiting the properties of concave programming and Slater's condition, the Lagrangian dual decomposition method is applied and an iterative algorithm that does not depend on the instantaneous channel state information (CSI) is proposed for solving the concave problem formulated. Extensive simulations demonstrate the efficacy and robustness of the proposed iterative algorithm. Furthermore, we show that the system's achievable EC does not depend on the specific choice of the subcarrier allocation, but rather on the number of subcarriers allocated to each user. This is, because, the EC is calculated using the channel's statistics, instead of the instantaneous CSI, implying that the EC is more of a long term channel capacity metric.

Keywords

• Spectral efficiency
• effective capacity maximization
• quality-of-service (QoS)
• delay-sensitive traffic
• Lagrangian dual decomposition
• OFDMA