Major challenges towards the development of next generation 4G wireless networks include fulfilling the foreseeable increase in power demand of future mobile terminals (MTs) in addition to meeting the high throughput and low latency requirements of emerging multimedia services. Studies show that the high-energy consumption of battery operated MTs will be one of the main limiting factors for future wireless communication systems. Emerging multimedia applications require the MTs’ wireless interfaces to be active for long periods while downloading large data sizes. This leads to draining the power of the batteries.

The evolution of MTs with multiple wireless interfaces helps to deal with this problem. This results in a heterogeneous network architecture with MTs that actively use two wireless interfaces: one to communicate with the base station (BS) or access point over a long-range (LR) wireless technology (e.g., UMTS/HSPA, WiMAX, or LTE) and one to communicate with other MTs over a short-range (SR) wireless technology (e.g., Bluetooth or WLAN). Cooperative wireless networks proved to have a lot of advantages in terms of increasing the network throughput, decreasing the file download time, and decreasing energy consumption at MTs due to the use of SR mobile-to-mobile collaboration (M2M). However, the studies in the literature apply only to specific wireless technologies in specific scenarios and do not investigate optimal strategies.

In this work, we consider energy minimization in content distribution with M2M collaboration and derive the optimal solution in a general setup with different wireless technologies on the LR and SR. Scenarios with multicasting and unicasting are investigated. Content distribution delay is also analyzed. Practical implementation aspects of the cooperative techniques are studied and different methods are proposed to overcome the practical limitations of the optimal solution. Simulation results with different technologies on the LR and SR are generated, showing significant superiority of the proposed techniques. Ongoing work is focusing on incorporating quality of service constraints in the energy minimization problem and in designing a testbed validating the proposed methods.


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