Continuously increasing the bandwidth to enhance the capacity is impractical because of the scarcity of spectrum availability. Fortunately, on the basis of the characteristics of the multihop cellular networks (MCNs), a new compact frequency reuse scheme has been proposed to provide higher spectrum utilization efficiency and larger capacity without increasing the cost on network. Base stations (BSs) and relay stations (RSs) could transmit simultaneously on the same frequency according to the compact frequency reuse scheme. In this situation, however, mobile stations (MSs) near the coverage boundary will suffer serious interference and their traffic quality can hardly be guaranteed. In order to mitigate the interference while maintaining high spectrum utilization efficiency, this paper introduces a fractional frequency reuse (FFR) scheme into multihop cellular networks, in which the principle of FFR scheme and characteristics of frequency resources configurations are described, then the transmission (Tx) power consumption of BS and RSs is analyzed. The proposed scheme can both meet the requirement of high traffic load in future cellular system and maximize the benefit by reducing the Tx power consumption. Numerical results demonstrate that the proposed FFR in compact frequency reuse achieves higher cell coverage probability and larger capacity with respect to the conventional schemes.

Being a new feature of next generation of wireless networks, Mobile Multi-hop Relay (MMR) is proposed for the purpose of coverage extension and throughput enhancement in LTE-Advanced, IEEE 802.16 j/m. Besides, with the help of relay, the system energy consumption could be well saved. In this paper, an energy saving scheduling scheme is proposed for OFDMA based two-hop relay systems. The novel scheme adjusts the modulation and coding (MC) mode and allocates the transmit power dynamically according to the resource intensity. It can also guarantee the Quality of Service (QoS) of different services by setting the scheduling priority. The simulation results show that the novel scheduling scheme can reduce energy consumption up to 76.27% compared to the conventional scheduling scheme, and achieve higher throughput while guaranteeing QoS.