FRONT-HAUL COMPRESSION FOR EMERGING C- RAN AND SMALL CELL NETWORKS

Transcription

1 FRONT-HAUL COMPRESSION FOR EMERGING C- RAN AND SMALL CELL NETWORKS April 29, Silver Creek Valley Road, San Jose, California Telephone: (408) Fax: (408)

2 OVERVIEW This document discusses how performance optimized compression offers significantly higher capacity between the Radio and the Baseband units in traditional RAN, emerging C-RAN and Small Cell Access Networks. Topics discussed include the following: Introduction Link Requirements and Deployment Scenarios Performance Requirements Performance Example Summary Key Words: Compression, Front-Haul, Base-Station, Cloud-RAN, Small Cell, RapidIO. 1. INTRODUCTION The vision of Small Cell and Centralized Radio Access Network (C-RAN) has recently generated significant interests among the research community, the device suppliers and the OEMs (Project C-RAN). The emerging architectures are expected to provide significant energy savings through a range of schemes, such as, network resource sharing, traffic off-loading, and interference management. The network architects can support a variety of network topologies based on the C-RAN concept. In particular, when deployed together with a macro- and micro-cellular network, the small cell architectures based on C-RAN are expected to provide significant CAPEX and OPEX savings, which in turn, could be translated to savings for the end-users. 2. LINK REQUIREMENTS AND DEPLOYMENT SCENARIOS To enhance the network capacity and the QoE, both a traditional and the emerging architectures shall support the higher data rate requirements offered by the LTE and LTE-Advanced protocols. These protocols offer significantly higher spectral efficiency through a range of PHY and MAC layer techniques, such as, Carrier Aggregation (CA), MIMO, Co-ordinated multi-point (CoMP), Interference Cancellation etc. In particular, LTE-A offers aggregation of up-to five 20-MHz LTE Carriers. When combined with MIMO, the CA techniques may lead up-to 100s of Gigabit/sec between the Radio and the Baseband units (i.e., the front-haul). Once the quantized I and Q samples are available, the receiver could apply a - 2 -

3 wide variety of interference cancellation, MIMO decoding, and CoMP algorithms to enhance the SNR in the network. Table 1 illustrates an example throughput calculation for a 3 sector LTE-A system with five 20 MHz carriers. Table 1. An example link rate calculation for a 3 sector cell with LTE-Advanced. Parameters Settings Units Sectors 3 LTE Carriers 5 Bandwidth 100 MHz MIMO 2x2 Tx-Rx Bits-per-I/Q 15 Bits Protocol LTE-A Throughput 13.8 Gbps To transport data in the front-haul, the operators may use the existing fiber or cable connections. Alternatively, the operators may rely on the emerging techniques, such as, front-haul over wireless links. The deployment decision is typically influenced by the infrastructure constraints. For example, in dense urban areas if it is difficult to deploy new fibers or requires zero foot-print solution, a wireless link might be more suitable. On the other hand, areas that already support fiber links, the operators may take advantage of the existing infrastructures. Regardless of the deployments, the equipment suppliers must provide cost-effective power efficient solution so that the operators can gracefully migrate to higher capacity systems. Such efficient solutions typically result from the utilization of low-cost optical connectors, savings in number of the links and improvements in spectral efficiency in the front-haul network. One possible way to achieve these savings is through data compression. For example with 2:1 front-haul compression in C-RAN and Small cell networks, it is possible to support a data rate of up-to Gbps while staying with an optical connector that supports only 2.5 Gbps. With low data rate optical connectors and less number of links, it is possible to reduce both cost and energy consumption. Furthermore, with such configuration, it is - 3 -

4 easy to transport 15-bit I and 15-bit Q samples for up-to 3 sectors with 2x2 MIMO and two LTE component carriers (one 10 MHz and one 20 MHz) in a system. This in-turn enables opportunity to apply advanced interference cancellation and load management techniques based on the quantized I and Q samples that leads to system level cost and energy savings in the radio access network. Figure 1 illustrates an example system architecture based on C-RAN and Small Cell with I 2 Q Compression. 3. PERFORMANCE REQUIREMENTS In addition to enhancing the spectral efficiency, the wireless protocols maintain certain signal quality (e.g., EVM) so that a particular QoE could be maintained in the network. On the other hand, depending on the modulation schemes, the EVM requirements may vary. Table 2 summarizes the LTE-A EVM requirements for various modulation schemes. Similar requirements exist for other wireless protocols, such as WCDMA, GSM etc. Table 2. EVM Requirements for various modulation schemes in LTE-Advanced [Section GPP TS ] Modulation Schemes EVM Requirements [%] QPSK 17.5% 16-QAM 12.5% 64-QAM 8% - 4 -

5 Figure 1. Traditional RAN, Emerging C-RAN and Small Cell System Architecture with I 2 Q Compression. SFP/ SFP+ CPRI/OBSAI Radio Card Processing FPGA/ASIC/SOC I 2 Q Compression Decompressor /Compressor User Core Downstream Functions : Remote Radio Head Baseband Processing FPGA/ASIC/SOC User Core Upstream Functions I 2 Q Compression Compressor/ Decompressor CPRI/OBSAI SFP/ SFP+ Baseband Cluster Baseband Card Baseband Card Baseband Card Macro Cell with Small Cell Overlay SOC SOC SOC RapidIO FPGA/ ASIC Transport Quantized I and Q Samples (Link between Radio and Baseband) - 5 -

6 4. PERFORMANCE EXAMPLE To provide a superior QoE, the Compression technology used in the front-haul network should meet the EVM requirements specified by the wireless protocols. Furthermore, the chosen Compression methods should keep enough margins for other modules in the signal chain so that the overall EVM performance could be achieved by the operators while achieving a higher throughput in the network. Figure 2 illustrates a typical 3GPP E-TM3.1 downlink signal spectrum and Table 3 summarizes the EVM performance of the I 2 Q data compression technology with typical E-TM3.1 downlink signal. In this example, a 20 MHz LTE-A signal is compressed and decompressed with an EVM of less than 1% RMS for a compression ratio of 2:1. This leaves enough margins for rest of the modules in the signal chain to meet the overall EVM requirements in the system. Figure 2. LTE Downlink 20-MHz Signal Spectrum and Performance with a Compression ratio of 2:

7 Table 3. IP Performance with typical LTE Downlink Signal. Parameters Values Downlink-Signal E-TM 3.1 Compression Technique I 2 Q Data Compression Average EVM 0.52% Bandwidth Protocol 20 MHz LTE-A 5. SUMMARY A variety of Compression techniques are being currently considered by a number of organizations and operators to gracefully migrate towards a system with larger capacity in traditional and emerging radio access networks. With superior EVM performance, it is possible to support data compression in wireless networks while keeping enough margins for other modules in the signal chain. Based on the available I and Q samples in a compression enabled solution, the system architects and the OEMs will have opportunity to optimize the system performance through a range of advanced signal processing and network resource sharing techniques in the emerging C-RAN and small cell networks

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