Antenna Selection in Multicarrier Communication Systems

Imagine a packet of data transmitted by radio frequency through the air. This packet appears at two separate antenna ports of a radio receiver. Even though the same data appear at both antennas, a different path in space is associated with each antenna. Any path in space results in signal power reduction and usually in a power redistribution in the allocated frequency band. Both effects enhance the error rate and reduce the reliability of the decoded data. The receiver usually supports the wireless link only through a single antenna due to cost considerations. This paper focuses on the particular case where the signal at one antenna is strong, but does not efficiently utilize the available frequency band, and at the other antenna the signal is weak, but uniformly distributed over the band. The paper provides a general algorithm for selecting the optimal antenna and explains both quantitatively and qualitatively which antenna should be selected. INTRODUCTION Multipath fading is a major limitation to high-rate data transmission in wireless communication systems. Fading is a result of destructive interference between replicas of the signal arriving through different paths. Another aspect of the same effect is an intersymbol interference. This occurs when the replicas merge again at the antenna and successive data symbols are mixed together, forming a mismatched symbol. Multicarrier communication methods overcome intersymbol interference by subdividing the allocated bandwidth into a few frequency sub-bands. At each carrier (sub-band), the data is transmitted using long symbol durations compared to the time delay between replicas. Thus, the impact of intersymbol interference is reduced. Transmitting the data simultaneously through all carriers results in an overall high rate of data transmission. However, destructive interference still distorts the data. Those carriers that are subjected to destructive interference have a low Signal-to-Noise Ratio (SNR). Low SNR at defective carriers is partly overcome by applying spatial diversity (antenna diversity). Receiving the data simultaneously through multiple antennas increases the detection reliability. However, full antenna diversity is an expensive solution. A more cost-saving solution is to use semi-diversity. This is accomplished by selecting only a single antenna out of a given set. This antenna should offer the most reliable detection. Selecting antenna is usually accomplished by considering total antenna power. This criterion is unsatisfactory because power is not the only factor that determines the performance of the receiver. In fact, the distribution of the power among carriers is critical as well. For example, take an antenna that has received a giant pulse of power. Most of it emerges in a single carrier. Selecting this antenna while the rest of the carriers suffer low SNR exhibits a high error rate. This paper provides a simple algorithm for choosing the best antenna from among several. The algorithm improves the reliability of the data recovery process. The central pillar of this algorithm is an information-capacitylike parameter for each of the carriers. Using this parameter, instead of estimating power alone, yields more useful information about the contribution of each carrier. The performance of the receiver, while equipped with each antenna, is predicted by combining the appropriate contributions over all the carriers. The antenna selection algorithm described in this paper was implemented inside Intel’s chipset that handles the IEEE 802.11a standard. The chipset provides wireless connectivity to mobile PCs and also serves Intel CentrinoTM mobile technology. The paper demonstrates the application of the algorithm by referring to a simplified system consisting of only two carriers. Full treatment of the IEEE standard, which also includes error-correction coding, is beyond the scope of this paper. However, the described principles are very Intel Centrino is a trademark of Intel Corporation or its subsidiaries in the United States and other countries. Intel Technology Journal, Vol. 7, Issue 2, May 2003 Antenna Selection in Multicarrier Communication Systems 51 relevant to practical systems. An effort was made to make the contents clear to technical staff who are not directly involved with communication. Thus, terms such as constellation points, Signal-to-Noise ratio, equalization and gain control are demonstrated explicitly in this paper. After mathematically constituting the relevant glossary of terms, the suggested antenna-selection algorithm is introduced. Finally, the algorithm is proved to be successful in predicting the performance of a receiver equipped with an arbitrary characteristics antenna. This is established by numerical simulation of decoding noisy data. RELEVANT GUIDELINES TO ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING As was previously mentioned, the main idea behind a multicarrier communication system is the division of a given frequency band into smaller frequency sub-bands. Orthogonal Frequency Division Multiplexing (OFDM) is a particular case of a multicarrier communication system, in which the frequency sub-bands overlap. This overlapping is not harmful due to the fact that the carriers are mathematically orthogonal. A good reason for using OFDM is its inherent immunity against narrowband interference. If a specific sub-band is severely disturbed due to multipath fading or interference, error-correction coding can still overcome the disturbance, thus preventing the entire link from failing, as is the case with a single carrier. Another reason for using OFDM concerns the complexity of the equalizer. Assuming that each sub-band is sufficiently narrow, the effect of the channel is taken into account by assigning only a single complex number to each carrier. In comparison to a single-carrier system, this simplifies the implementation of the equalizer to a great extent. More extensive explanations about the principles of OFDM are documented elsewhere [1]. However, a few more guidelines are presented here to help clarify the information in the remaining part of this paper. Following IEEE standard 802.11a, all carriers that constitute a single data frame are subjected to the same modulation scheme: QAM constellation with a given order. The data is encoded by assigning a specific binary combination to each of the constellation points. This process is demonstrated in the next section. Thus, a single constellation point is determined for each frequency subband. Synthesizing the sequence of constellation points into a time domain signal is accomplished by Inverse Fourier Transformation. The inverse process takes place at the receiver. The time domain signal is transformed back to the frequency domain by means of Discrete Fourier Transform. Identifying which constellation point was assigned by the transmitter to each frequency band constitutes the demodulation process. Recognizing the correct point despite the noise and the channel fading is vital for successfully receiving the data. Finally the data is extracted by decoding the constellation points back into binary. DEFINITION OF A SIMPLIFIED SYSTEM In order to clarify our strategy, let us assume a simplified multicarrier communication system, which uses only two carriers. That is, the allocated frequency band is only divided into two sub-bands. At each sub-band information is modulated by the well-known Quadrature Phase-Shift Keying (QPSK) method. Figure 1 presents the constellation plane for QPSK and our preferred encoding scheme. Figure 1: Bits encoding scheme for QPSK constellation Suppose that the sequence to be delivered is “1110.” For simplicity, we assume that no error-correction coding is applied. Encoding this sequence results in two complex numbers: 1+j and 1-j, which comprise the baseband representation of this message. The transmitter combines these two complex numbers into a waveform in the time domain by using the Inverse Fourier Transformation. This waveform finally modulates the amplitude and phase of the RF carrier that is transmitted through the air. Demodulation and Noise At the receiver the reverse process is taking place, which results in measured points in the constellation plane. However, the constellation points measured by the receiver are corrupted by noise. This noise cannot completely be avoided, no matter what the quality of the receiver is. Once the message is transmitted the receiver measures two constellation points, (I1,Q1) and (I2,Q2), in carriers “1” and “2,” respectively. Although the exact values 1+j and 1-j were sent by the transmitter, this would never be the case with the measured values, due to the noise. Since no error-correction coding was applied, demodulation is carried out just by assigning each 00 -j j 01