An efficient data transmission policy in an integrated voice-data ds-cdma network

CDMA schemes appear to be promising access techniques for coping with the requirements of third-generation mobile systems, mainly because of their flexibility. This paper proposes an adaptive S-ALOHA DS-CDMA access scheme as a method for integrating non-real time (i.e. Internet applications) and real-time (i.e. voice) services, by exploiting the potentials of CDMA under time-varying conditions. The adaptive component terminals autonomously change their transmission rate according to the total (voice+data) channel occupancy, so that the minimum possible data delay is almost always achieved.Peer ReviewedPostprint (published version

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

Protocols for voice/data integration in a CDMA packet radio network.

Thesis (Ph.D.)-University of Natal, Durban, 1999.Wireless cellular communications is witnessing a rapid growth in, and demand for, improved technology and range of information types and services. Future third generation cellular networks are expected to provide mobile users with ubiquitous wireless access to a global backbone architecture that carries a wide variety of electronic services. This thesis examines the topic of multiple access protocols and models suitable for modem third-generation wireless networks. The major part of this thesis is based on a proposed Medium Access Control (MAC) protocol for a Code Division Multiple Access (CDMA) data packet radio network, as CDMA technology is proving to be a promising and attractive approach for spectrally efficient, economical and high quality digital communications wireless networks. The proposed MAC policy considers a novel dual CDMA threshold model based on the Multiple Access Interference (MAl) capacity of the system. This protocol is then extended to accommodate a mixed voice/data traffic network in which variable length data messages share a common CDMA channel with voice users, and where the voice activity factor of human speech is exploited to improve the data network performance. For the protocol evaluation, the expected voice call blocking probability, expected data throughput and expected data message delay are considered, for both a perfect channel and a correlated Rayleigh fading channel. In particular, it is shown that a significant performance enhancement can be made over existing admission policies through the implementation of a novel, dynamic, load-dependent blocking threshold in conjunction with a fixed CDMA multiple access threshold that is based on the maximum acceptable level of MAl

Automatic best wireless network selection based on key performance indicators

Introducing cognitive mechanisms at the application layer may lead to the possibility of an automatic selection of the wireless network that can guarantee best perceived experience by the final user. This chapter investigates this approach based on the concept of Quality of Experience (QoE), by introducing the use of application layer parameters, namely Key Performance Indicators (KPIs). KPIs are defined for different traffic types based on experimental data. A model for an ap- plication layer cognitive engine is presented, whose goal is to identify and select, based on KPIs, the best wireless network among available ones. An experimenta- tion for the VoIP case, that foresees the use of the One-way end-to-end delay (OED) and the Mean Opinion Score (MOS) as KPIs is presented. This first implementation of the cognitive engine selects the network that, in that specific instant, offers the best QoE based on real captured data. To our knowledge, this is the first example of a cognitive engine that achieves best QoE in a context of heterogeneous wireless networks

Prediction-Based Energy Saving Mechanism in 3GPP NB-IoT Networks

The current expansion of the Internet of things (IoT) demands improved communication platforms that support a wide area with low energy consumption. The 3rd Generation Partnership Project introduced narrowband IoT (NB-IoT) as IoT communication solutions. NB-IoT devices should be available for over 10 years without requiring a battery replacement. Thus, a low energy consumption is essential for the successful deployment of this technology. Given that a high amount of energy is consumed for radio transmission by the power amplifier, reducing the uplink transmission time is key to ensure a long lifespan of an IoT device. In this paper, we propose a prediction-based energy saving mechanism (PBESM) that is focused on enhanced uplink transmission. The mechanism consists of two parts: first, the network architecture that predicts the uplink packet occurrence through a deep packet inspection; second, an algorithm that predicts the processing delay and pre-assigns radio resources to enhance the scheduling request procedure. In this way, our mechanism reduces the number of random accesses and the energy consumed by radio transmission. Simulation results showed that the energy consumption using the proposed PBESM is reduced by up to 34% in comparison with that in the conventional NB-IoT method