Evolution and Interference Analysis of Cooperative Communication Systems

Release Date:2010-03-21  Author:Sun Huixia  Click:


This work was supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China under Grant No. 2009ZX03003.


1 Background and Principles  of Cooperative Communication
Long Term Evolution (LTE) technology is a well-designed, advanced technology. First, in wireless access networks, with downlink Orthogonal Frequency Division Multiplexing (OFDM) and uplink Discrete Fourier Transform Spread OFDM (DFT-SOFDM) techniques, complete orthogonal channel in the cell can be obtained. This greatly reduces co-cell interference. Second, multi-antenna technologies such as transmit/receive diversity, Space Division Multiplexing (SDM) and beamforming, can be flexibly used to exploit the characteristics of spatial channel, increase the throughput, and overcome interference. Third, the Inter-cell Interference Coordination (ICIC) mechanism marks a conceptual breakthrough: A single cell is no longer separately controlled. It treats multiple cells as a large system and introduces the concept of joint coordination interference. Therefore, the link traffic of an LTE system almost approaches the Shannon limit. In the future evolution of LTE systems, higher spectrum efficiency will be required[1]; however currently, little can be done to improve link-level technologies. To improve link performance, cooperative communication technology is introduced into LTE systems as a possible solution.

    Cooperative communication technology allows systems to implement multi-point transmission and reception between eNodeBs, or simultaneously between eNodeB and Remote Radio Units (RRUs). With this technology, User Equipment (UE) can establish uplink and downlink with multiple eNodeBs and RRUs for communication. The eNodeBs and RRUs are interconnected with optical fibers, as shown in Figure 1. Cooperative communication occurs in two forms: Coordinated Multi-Point (CoMP) transmission and inter-eNodeB coordination. In CoMP, a distributed antenna system[2] is formed by adding RRUs in the network or by using existing eNodeBs, which enables multi-point transmission and reception between eNodeBs and UEs. In inter-eNodeB coordination, all eNodeBs in the existing network are directly connected with optical fibers, enabling multiple eNodeBs to directly communicate with UEs. Both forms of coordination are practical applications of cooperative communication technology in reality.


    Cooperative communication mainly takes advantage of system processing gains. To achieve such gains from multi-point cooperation, multi-point cooperation issues have to be considered in specific technologies. Currently, several key technologies are being researched:

    (1) Intelligent correlation. A UE can automatically search the transmitting eNodeB with the least path loss to access.

    (2) Load balancing among eNodeBs. The service load in the coverage area is shared by multiple eNodeBs. In this technology, inter-eNodeB communication is required to coordinate load sharing and learn resource usage.

    (3) Multiple Input Multiple Output (MIMO). All eNodeBs in the coverage can adopt different MIMO schemes. For example, in the area covered by several eNodeBs, different users can access the same frequency at the same time. The users’ beams, however, have to be shaped by different eNodeBs respectively in order to identify them and improve spectrum efficiency.

    (4) Selection of cooperative eNodeBs. An appropriate number of eNodeBs and their locations should be selected to realize optimal cooperation.

    (5) Dynamic ICIC[3]. In multi-eNodeB cooperative communication, eNodeBs connected with optical fibers can achieve fast data communication. Therefore, dynamic ICIC technology can be implemented to coordinate inter-cell interference.

2 Network Evolution


2.1 Network Evolution with Cooperative Communication Technology
In classic macro cellular networking schemes, NodeBs and microcells are often configured to construct a hierarchical hybrid network, in which NodeBs are used for continuous coverage, while microcells are used to cover hot spots and blind areas. In other words, microcells can share the traffic load with macrocells and supplement macrocells by covering their coverage holes and blind areas. For example, in R8 LTE systems, macrocells and microcells provide hierarchical network coverage. The systems use a Soft Frequency Reuse (SFR) scheme in frequency planning for multiple cells, as well as for macro and microcells. Figure 2 shows a network constructed in such a way.


    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.

3 Conclusions
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.


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[Abstract] Frequency division design sacrifices the built-in macrodiversity gains of 3G systems, making it difficult to fully exploit the advantages of Long Term Evolution (LTE) technology. As a result, for LTE Advanced (LTE-A), cooperative communication technology is proposed. System-level cooperative communications can maximize system performance. To achieve system-level gains, high spectrum efficiency and reliable performance, cooperative communication technology is required. With the introduction of technologies such as multi-point transmission/reception, intelligent relay, and cooperative antenna, LTE-A system’ coverage is enhanced. The handover between user terminals can also be stably realized and the traffic and Quality of Service (QoS) in handover areas improved.


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