Abstract
In recent years, user cooperative traffic forwarding is a popular study topic and broadly seen as one of the important promising technologies to improve energy efficiency (EE) of the battery-driven mobile terminal (MT). However, the battery-driven devices always suffer from a problem of limited working time due to battery life. In this paper, we propose a simply machine learnable bandwidth allocation strategy for user cooperation-aided wireless communication systems and evaluate the power consumption of the systems via both theoretical and experimental approaches. By using the proposed bandwidth allocation strategy, we first derive the mathematical expressions to evaluate the transmission power of the MTs for non-cooperative and cooperative scenarios by a generalized channel model. In this generalized model, the spatially correlated shadowing and frequency selective fading are considered as channel effects, and this generalized model is mathematically analyzed for the consumed power via the proposed scenarios with the long-term evolution (LTE) power model for smartphones. In the final stage, we evaluate the results by our smartphone test-bed. The results obtained in this paper show that the benefits of the user cooperation-aided traffic forwarding are significant. Unfortunately, according to the numerical analysis, because there are some physical constraints for MTs, such as maximal transmit power, we cannot drastically obtain the benefits in real application cases. Some interesting points, such as how to use a machine learning approach to reduce the system complexity and thus improve transmission performances, are also discussed in this paper.
Highlights
Because of the rapid and explosive development of wireless applications [1], recently the mobile terminals (MTs) are very popular and important to modern people for various kinds of network communication demands in cellular systems, for example, high-definition video streaming, online gaming for multiple users, and instant text messaging, etc
In order to lower this kind of transmission loading and improve the performance of power saving for each MT in an effective and efficient way, forwarding transmission by utilizing cooperative wireless methods among MTs, which is called user cooperation or cooperative communications, is widely considered and investigated as a promising approach to solve these issues [2], [3]
From the results shown above, it can be seen that, the power consumption can be significantly reduced by using user cooperation aided forwarding technique over frequency selective fading channel, and the proportion of power consumption reduction is getting larger with the increase of total communication demand
Summary
Because of the rapid and explosive development of wireless applications [1], recently the mobile terminals (MTs) are very popular and important to modern people for various kinds of network communication demands in cellular systems, for example, high-definition video streaming, online gaming for multiple users, and instant text messaging, etc. According to the discussion above, in this study, we propose a machine learnable bandwidth allocation strategy for user cooperative traffic forwarding, and evaluate the power consumption of the systems by both theoretical and experimental methods. Theorem 2: With the consideration of U frequency selective SIMO channels with channel selection, for cooperative transmission forwarding scenario, if each SIMO channel and its L sub-channels experience spatially i.i.d. Rayleigh fading and spatially correlated shadowing with correlation matrix s, the ergodic capacity is given by (10), as shown at the bottom of this page, where (ω) is given by (11), fλu (λ), Fλu (λ) can be calculated by the following expression fλu (λ). Proof: For brevity, we defer the proof in Appendix B
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
