Downlink scheduling in CDMA data networks

  • Authors:
  • Niranjan Joshi;Srinivas R. Kadaba;Sarvar Patel;Ganapathy S. Sundaram

  • Affiliations:
  • wireless Technology Laboratory, Lucent Technologies, Whippany, NJ;wireless Technology Laboratory, Lucent Technologies, Whippany, NJ;wireless Technology Laboratory, Lucent Technologies, Whippany, NJ;wireless Technology Laboratory, Lucent Technologies, Whippany, NJ

  • Venue:
  • MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
  • Year:
  • 2000

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Abstract

Packet data is expected to dominate third generation wireless networks, unlike current generation voice networks. This opens up new and interesting problems. Physical and link layer issues have been studied extensively, while resource allocation and scheduling issues have not been addressed satisfactorily.In this work, we address resource management on the downlink of CDMA packet data networks. Network performance (for example, capacity) has been addressed, but user centric performance has not received much attention. Recently, various non-traditional scheduling schemes based on new metrics have been proposed, and target user performance (mostly without reference to wireless). We adapt these metrics to the CDMA context, and establish some new results for the offline scheduling problem. In addition, we modify a large class of online algorithms to work in our setup and conduct a wide range of experiments. Based on detailed simulations, we infer that:Algorithms which exploit “request sizes” seem to outperform those that do not. Among these, algorithms that also exploit channel conditions provide significantly higher network throughput.Depending on continuous or discretized bandwidth conditions, either pure time multiplexing or a combination of time and code multiplexing strikes an excellent balance between user satisfaction and network performance.Discrete bandwidth conditions can lead to degraded user level performance without much impact on network performance. We argue that the discretization needs to be fine tuned to address this shortcoming.