To minimize co-frequency interference in the adjoining areas between cells or between macrocells and microcells, most existing systems adopt an SFR scheme to ensure the cells use different sub-bands at the edge of the overlapped coverage area and apply Frequency Division Multiplexing (FDM) to resist co-frequency interference. But this method may bring about the following problems:
(1) Spectrum efficiency losses: FDM mitigates interference at the cost of spectrum efficiency.
(2) Communication quality suffers: When a UE moves to the edge of a cell, its frequency band has to be changed offen. This degrades link adaption performance during frequency scheduling, and thus reduces communication quality.
(3) This performance of this method largely depends on division of the center (interior) and the edge (exterior); each division scheme has an impact on system performance. To meet the rate and load demands for various scenarios, the ICIC algorithm must be very complicated which, in turn, increases the load of each eNodeB.
After multi-eNodeB cooperative communication technology is adopted, eNodeBs become interconnected with optical fibers. One of them acts as the master eNodeB, used for service communication, while the others are degraded into RRUs, used for simultaneous multi-point transmission and reception. In this case, the coverage of the master eNodeB is enlarged and handover areas are minimized. The traditional hierarchical network coverage is transformed into large-cell coverage, with the load being shared by several eNodeBs (as shown in Figure 3). In large-cell coverage, multi-point transmission/reception not only extends uplink/downlink coverage distances but also improves macrodiversity gains. This is similar to soft handover in 3G systems because the UE selects the eNodeB with the least path loss to access. Consequently, the coverage performance is improved in terms of capability, quality and probability. Moreover, when the scheduling algorithm and multi-eNodeB coordination algorithm is applied in cooperative communication technology, service loads in the large cell can be dynamically shared by several eNodeBs. All services in the large cell can be supported, and each UE can randomly select the eNodeB with the best signal quality to access. When a UE moves in the coverage areas of the master eNodeB and RRUs, it seems to move in the coverage area of one eNodeB. As a result, quick and stable handover is achieved, better Quality of Service (QoS) is experienced, and spectrum efficiency and service performance are considerably improved. The complexity of ICIC algorithm is also reduced.
2.2 Interference Analysis
In a multi-eNodeB cooperative communication system, the master eNodeB not only communicates with all UEs within its coverage and connected to it, but also coordinates resource usage with other eNodeBs that degrade into RRUs. Hence, inter-cell uplink/downlink co-frequency interference is greatly mitigated, and approximate orthogonality can even be achieved. In such a situation, the system interference mainly comes from remote cooperative eNodeBs.
Let’s compare a simple LTE system model and a cooperative communication system model to analyze the interference. Figure 4(a) is a R8 LTE network, where each cell suffers
co-frequency interference from its neighbors. Figure 4(b) is a multi-eNodeB cooperative communication network, where three eNodeBs form a multi-point cooperative communication group and each group suffers co-frequency interference from other groups. The following is our analysis of uplink/downlink interference distribution within the coverage of eNodeB in the two systems.
Table 1 lists the basic parameters for interference analysis. Without any other technologies (e.g. anti-interference of smart antenna system or interference coordination technology), the interference distributions of the two systems in uplink and downlink can be represented by Figures 5 and 6 respectively. Figure 5 is the interference distributions, represented by Cumulative Distribution Function (CDF) curves, of the two systems in the downlink coverage. Figure 6 is the interference distributions in the uplink coverage. As shown in the two figures, the cooperative communication system’s interference is less than an existing R8 system’s by some degree; specifically, about 2dB in the downlink and 2-4 dB in the uplink.
The scenario used here for analysis is a simple one, and the cooperative communication system brings about a slight decrease in interference. In reality, however, the interference may be greatly mitigated if proper macrocells and microcells are selected for cooperation. With the application of antenna downtilt, ICIC, and multi-antenna technologies, inter- and intra-cell interference in the cooperative communication network will approximate orthogonality. This will greatly decrease the impact of interference on system throughput and improve spectrum efficiency.
Despite substantial system gains brought about by cooperative communication technology, there are still many issues to be studied before the advantages of the technology can be fully exploited. For instance:
(1) Coverage of signaling channel: Multi-eNodeB cooperative transmission enlarges the coverage of a single eNodeB, but how the control channel can achieve good coverage performance in the entire coverage area is still a problem.
(2) System load sharing: How to effectively share the load among several eNodeBs in a large coverage area must be further studied. The sharing will increase signaling streams between eNodeBs.
(3) Dynamic ICIC: Dynamic ICIC involves much inter-eNodeB communication, which increases with the number of eNodeBs.
The above problems are critical to the application of cooperative communication technology.
This paper analyzes the principles of cooperation communication systems and the evolution of existing LTE R8 systems to cooperative communication networks. It also compares the interference of cooperative communication networks with existing LTE networks. Analysis results show that cooperative communication technology, compared with non-cooperative technologies, can greatly improve coverage, interference, and throughput[4-8]. Its application makes LTE a particularly advanced system. This technology not only meets current service demands and probably service demands into the future, but may also introduce new services that will mark a new era in the development of mobile data communications.
 3GPP TR36.913 V8.0.1. 3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Requirements for Further Advancements for Evolved Universal Terrestrial Radio Access (E-UTRA) (LTE-advanced) (Release 8) [S]. 2009.
 ZHU Jinkang. Wireless Mesh technology and network [J]. ZTE Communications, 2008,6(2): 1-6.
 沈嘉, 索士强, 全海洋, 等. 3GPP长期演进(LTE)技术原理与系统设计 [M]. 北京: 人民邮电出版社, 2008. SHEN Jia, SUO Shiqiang, QUAN Haiyang, et al. 3GPP long term evolution: principle and system design [M]. Beijing: Posts & Telecommunications Press, 2008.
 CHEN Linlin, LIU Naian. Wireless Mesh network and IEEE 802 standards [J]. ZTE Communications, 2008, 6(2): 7-10.
 TIAN Hui, TAO Xiaofeng. Wireless Mesh architecture for IP-based base stations [J]. ZTE Communications, 2008, 6(2): 15-19.
 JIANG Xiaokui. Wireless Mesh networks and cooperative relaying technologies [J]. ZTE Communications, 2008, 6(2): 20-24.
 WU Fan, MAO Yuming, ZHANG Ke. Key technologies of wireless Mesh network [J]. ZTE Communications, 2008, 6(2): 25-29.
 LIU Tianxi, TANG Xiaotong, JIAO Bingli.
Quorum-based energy conserving mechanism in wireless Mesh networks [J]. ZTE Communications, 2008, 6(2): 34-38.