International audienceCoordinated Multi-Point (CoMP) transmission for LTE-Advanced systems promises enhanced throughput and coverage performance, especially for cell edge users. However, the performance of CoMP systems heavily depends on the feedback quality and channel imperfections. In this paper, we investigate the impact of quantized and delayed channel state information (CSI) on the average achievable rate of joint transmission (JT) and coordinated beamforming (CBF) systems. We derive closed-form expressions and accurate approximations on the expected sum rate of CoMP systems with imperfect CSI assuming small-scale Rayleigh fading, pathloss attenuation, and other-cell interference (OCI). Furthermore, for analytical tractability, we employ a moment matching technique that approximates the distributions of the received desired and interference signals. Based on our analytical framework, we show that CBF and JT to multiple users are more sensitive to CSI imperfections than single-user JT and we identify switching points and optimal operating regimes for each scheme. Furthermore, we propose an adaptive multimode transmission technique that switches between CoMP schemes to maximize the sum rate. Finally, the proposed approximate framework enables us to identify key system parameters, such as feedback resolution, delay, pathloss, and transmit SNR for which CoMP becomes a judicious choice of transmission strategy as compared to non-cooperative transmission
Coordinated Multi-Point (CoMP) transmission is a promising technique for LTE-Advanced systems, especially due to the enhanced throughput performance of cell edge users. In this paper, we investigate joint transmission (JT) and coordinated beamforming (CBF) with quantized and delayed feedback, and we derive ergodic rate and outage probability expressions assuming large-scale fading (pathloss), small-scale Rayleigh fading, and other-cell interference (OCI). Furthermore, we employ a moment matching technique that approximates the distributions of the received desired and interference signals with Gamma distributions as a means to facilitate analysis and simulation. The performance of CoMP transmission is quantified and compared with non-cooperative transmission, and operating regions in which CoMP gains are more pronounced are provided. The versatility of the proposed approximate framework enables us to identify key system parameters, such as feedback resolution, pathloss, and transmit SNR for which CoMP becomes a judicious choice of transmission strategy.
Limited-Stop (LS) bus services have recently proved to be essential for improving user welfare and reducing operators’ costs in many cities. The design of LS services has been mainly focused on increasing fleet efficiency and reducing the passengers’ travel time. In this work, we change the focus of LS service design towards the user’s comfort. Given a fixed-size fleet (fixed costs) and a fixed demand on a very high-frequency bus corridor, we propose an algorithm to minimize the peak load profile, combining the usual All-Stop (AS) and one additional LS service, finding the set of stops for the LS service and the fleet split. The strategy is proved in a set of statistically generated corridors, showing average capacity reductions > 20% at a cost of a marginal travel time increase. Analyzing the peak value in the load profile of all simulated corridors, the number of cases where the majority of users would find a seat on the bus increases from 15% to 53%, making the services much more attractive without increasing the costs.
The evolution of IoT has come with the challenge of connecting not only a massive number of devices, but also providing an always wider variety of services. In the next few years, a big increase in the number of connected devices is expected, together with an important increase in the amount of traffic generated. Never before have wireless communications permeated so deeply in all industries and economic sectors. Therefore, it is crucial to correctly forecast the spectrum needs, which bands should be used for which services, and the economic potential of its utilization. This paper proposes a methodology for spectrum forecasting consisting of two phases: a market study and a spectrum forecasting model. The market study determines the main drivers of the IoT industry for any country: services, technologies, frequency bands, and the number of devices that will require IoT connectivity. The forecasting model takes the market study as the input and calculates the spectrum demand in 5 steps: Defining scenarios for spectrum contention, calculating the offered traffic load, calculating a capacity for some QoS requirements, finding the spectrum required, and adjusting according to key spectral efficiency determinants. This methodology is applied for Colombia’s IoT spectrum forecast. We provide a complete step-by-step implementation in fourteen independent spectrum contention scenarios, calculating offered traffic, required capacity, and spectrum for cellular licensed bands and non-cellular unlicensed bands in a 10-year period. Detailed results are presented specifying coverage area requirements per economic sector, frequency band, and service. The need for higher teledensity and higher spectral efficiency turns out to be a determining factor for spectrum savings.
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