High Speed Downlink Packet Access User Research Articles

A Performance Model for the HSDPA User Equipment and its Validation

A new queuing model is proposed for the performance evaluation of the High Speed Downlink Packet Access (HSDPA) protocol, with respect to a specified user, in UMTS networks. This analytical model is an integrated one capable of capturing many complicated features of HSDPA operation such as correlated and bursty traffic, channel fading, channel allocation policy and packet-losses in the air interface. The validation of the model for comparing the user terminal categories is performed with a detailed simulation of HSDPA terminals with "real" traffic traces. It is shown that the model is quite accurate to predict and compare the throughput of the HSDPA terminal categories.

A Markovian queue with varying number of servers and applications to the performance comparison of HSDPA user equipment

Inspired by the need for performability models for HSDPA user equipment, a Markovian queue with varying number of servers is conceived. The arrival and the service processes, the number of allocated or active servers of the queue are inherently, and independently (or jointly) Markov modulated. Batch arrivals, batch services, autocorrelation of inter-arrival times, and autocorrelation of batch sizes can be accommodated in the queue, by a suitable use of Markov modulation and generalized exponential distribution. The queue has a provision for negative customers too. Transformations of the balance equations into a computable form are proposed in order to obtain the steady state probabilities with the Spectral Expansion method. This queue is used to model the High Speed Downlink Packet Access (HSDPA) wireless networks. The model is an integrated one with respect to HSDPA, capable of accommodating many of the intricate aspects of HSDPA such as, channel allocation policy, loss of packets due to channel fading, bursty and correlated traffic. Good agreement is observed between the numerical results of the proposed analytical model and those of an independent simulator of real HSDPA and radio channel behaviors. The comparison of the terminal categories specified by the 3rd Generation Partnership Project (3GPP) is also presented.

Spatial and Temporal Fairness in Heterogeneous HSDPA-Enabled UMTS Networks

The system performance of an integrated UMTS network with both High-Speed Downlink Packet Access users and Release '99 QoS users depends on many factors like user location, number of users, interference, multipath propagation profile, and radio resource sharing schemes. Additionally, the user behavior is an important factor; users of Internet best-effort applications tend to follow a volume-based behavior, meaning they stay in the system until the requested data is completely transmitted. In conjunction with the opportunistic transmission scheme implemented in HSDPA, this has implications to the spatial distribution of active users as well as to the time-average user and cell throughput. We investigate the relation between throughput, volume-based user behavior and traffic dynamics with a simulation framework which allows the efficient modeling of large UMTS networks with both HSDPA and Release '99 users. The framework comprises an HSDPA MAC/physical layer abstraction model and takes network aspects like radio resource sharing and other-cell interference into account.

Opportunistic scheduling for streaming multimedia users in high-speed downlink packet access (HSDPA)

High-speed downlink packet access (HSDPA) achieves high data rates and high spectral efficiency by using adaptive modulation and coding schemes and employing multicode CDMA. In this paper, we present opportunistic algorithms for scheduling HSDPA users and selecting modulation/coding and multicode schemes that exploit channel and buffer variations to increase the probability of uninterrupted media play-out. First, we introduce a stochastic discrete event model for a HSDPA system. By employing the discrete event model, we transform the scheduling problem of providing uninterrupted play-out to a feasibility problem that considers two sets of stochastic quality-of-service (QoS) constraints: stability constraints and robustness constraints. A methodology for obtaining a feasible solution is then proposed by starting with a so-called stable algorithm that satisfies the stability QoS constraints. Next, we present stochastic approximation algorithms that adapt the parameters of the stable algorithm in a way that a feasible point for the robustness QoS is reached within the feasibility region of the stability QoS