Figure 1. Omni and Sectorized Antennas System
Demand for more mobile broadband high-speed data services and reliable voice service continues to increase. In response, mobile operators continuously enhance their spectrum efficiency and increase their network capacity, reducing overall network OPEX and increasing network service robustness. Multiple antenna technology or Multiple-Input Multiple Output (MIMO) improves spectral efficiency and has been widely adopted in modern wireless systems.
Interference Limited Systems
In the crowded channel scenario, increasing traffic throughput by boosting basestation transmission power or using high-order modulation would degrade the system capacity and signal quality due to increased interference. These systems are called interference limited.
For example, when a basestation uses omni-directional antennas (see Figure 1a), the transmission/reception of each user's signal becomes a source of interference to other users located in the same cell. Therefore, the overall system becomes interference limited. Sectorized antennas can effectively reduce this interference; the cell is split into multiple sectors with separate antennas as shown in Figure 1b. All modern wireless systems, at a minimum, use sectorization to reduce interference and increase capacity.
Figure 2. Smart Antenna System—Beamforming
Sectorized antennas, even though they incorporate frequency diversity, are a static form of multiple antenna technology. Advanced multiple antenna or MIMO technologies—such as adaptive beamforming, Space Division Multiple Access (SDMA) and Space Time Coding (STC)—are used in today’s wireless systems or are planned for upcoming wireless infrastructure systems.
Beamforming, an advanced multiple-antenna technology, reduces interference levels and improves system capacity even further. With this technology, each user's signal is transmitted and received from and to the direction of that particular user within the same band. Combined with advanced (smart) signal processing solutions, beamforming significantly reduces overall interference. Figure 2 illustrates an example beaming system, consisting of an antenna array.
In beamforming, each user's signal is multiplied with complex weights that adjust the magnitude and phase of the signal to and from each antenna. As a result, the antenna array output forms a transmit/receive beam in the desired direction and minimizes the output in other directions.
Space Division Multiple Access (SDMA)
Similar to beamforming, the SDMA creates parallel spatial pipes through spatial multiplexing and/or diversity in the channel scenarios of existing rich independent multiple paths. This method offers superior system performance and throughput. By using smart antenna technology and the different spatial locations of the mobile users within the cell, SDMA can convert the system from interference limited to noised limited, achieving a much higher channel spectrum efficiency.
Space Time Coding (STC)
MIMO architectures that use STC encodes a data stream onto spatial and time patterns either orthogonally or non-orthogonally . This technique is sometimes referred to as diversity coding. By transmitting multiple copies of the same data—each with a different code—signal processing techniques at the receiver can maximize the signal quality and provide higher spectral efficiency vs. non-MIMO architectures.
MIMO Implementation with Intel® FPGAs
Intel's Arria® and Stratix® series FPGAs feature high-performance, digital signal processing (DSP) blocks and logic elements (LEs), making them ideal for smart antenna technology applications. Additionally, the dual-core ARM* Cortex*-A9 MPCore* processor and/or the NEON acceleration unit can implement adaptive DSP algorithms.
Many beamforming architectures and adaptive algorithms provide good performance under different scenarios, such as transmit-receive adaptive beamforming and transmit-receive switched beamforming. With embedded processors and easy-to-use development tools, such as the DSP Builder for Intel® FPGAs and the Platform Designer (formerly Qsys), Intel FPGAs offer a high degree of flexibility for implementing adaptive signal processing algorithms.
The standards for next-generation networks are continuously evolving with complex multiple antenna technology adoption, creating an element of risk for ASIC implementation. Because Intel FPGAs are remotely upgradeable and scalable, they reduce the time to market and risk of designing efficient solution for the evolving industry standards while providing the option for the gradual incremental deployment of additional MIMO schemes.