Introduction to link adaptation

Link adaptation, or adaptive coding and modulation (ACM), is a term used in wireless communications to denote the matching of the modulation, coding and other signal and protocol parameters to the conditions on the radio link.

Adaptive modulation systems invariably require some channel state information at the transmitter. This could be acquired in time division duplex systems by assuming the channel from the transmitter to the receiver is approximately the same as the channel from the receiver to the transmitter.

Alternatively, the channel knowledge can also be directly measured at the receiver, and fed back to the transmitter. Adaptive modulation systems improve rate of transmission, and/or bit error rates, by exploiting the channel state information that is present at the transmitter. Especially over fading channels which model wireless propagation environments, adaptive modulation systems

exhibit great performance enhancements compared to systems that do not exploit channel knowledge at the transmitter.

2.2.1 Literature review of Link Adaptation

Link adaptation has been widely studied in different types of wireless communication systems. Below was attempted to collect key publications about aforementioned subject. Link adaptation was first proposed in 1997 from Sampath, Sarath Kumar, Holtzman, in which an analytical outer loop power control model was studied to handle the Signal-to-Interference Ratio (SIR) fluctuation. In 2013 Li in his paper ``Cooperative uplink link adaptation in 3GPP LTE heterogeneous networks,'' investigated the impact of uplink interference on the efficiency of link adaptation in heterogeneous networks, and they further proposed a cooperative uplink link adaptation scheme by exploiting the cooperation among base stations. Durn (2015) designed a novel self-optimization algorithm for improving the convergence speed of the outer loop link adaptation (OLLA) in the downlink of LTE systems. Xia (2009) proposed the Auto-Rate Fallback for High-Throughput (ARFHT) algorithm for the emerging high- throughput IEEE 802.11n wireless networks, that extends the legacy link adaptation algorithms for Single-Input-Single-Output (SISO) wireless networks to Multiple-Input-Multiple-Output (MIMO)-based 802.11n wireless networks.

Cavalcante (2016) in the paper ``On the system-level analysis of outer loop link adaptation for IEEE 802.16e systems,'' provided a system-level analysis of OLLA for IEEE 802.16e systems. Sarret (2015) proposed a dynamic OLLA (d-OLLA) algorithm to address the large Signal-to-Interference plus Noise Ratio (SINR) fluctuation for 5G of wireless communication systems. Blanquez-Casado (2016) provided a thorough analysis of OLLA, including its dynamics and convergence conditions. Based on the analysis, they proposed an enhanced OLLA (eOLLA) scheme to adaptively modify the step size and to update the offset according to the reception conditions.

2.2.2 Link adaptation in LTE

Link adaptation in LTE systems dynamically adjusts the data rate of transmitted information (modulation scheme and channel code rate) to equalize the existing radio channel capacity assigned for each user. Link adaptation is therefore closely related to the channel code scheme project used for forward error (FEC).

2.2.3 Downlink transmission

For downlink data transmission in LTE systems, the Base Station or Evolved Node B (eNodeB) usually selects the modulation scheme and the code rate depending on the prediction of the downlink channel conditions [3]. An important piece of information for this selection process is the Channel Quality Indicator (CQI) feedback transmitted by the User Equipment (UE) in the uplink channel. CQI feedback is an indicator of the data rate that the channel can support, taking into consideration the Signal to Interference plus Noise Ratio (SINR) and the receiving characteristics of the UE [4, 5, 6]. This chapter explains the link adaptation principles applied to the LTE system. It will also show how the eNodeB can select one of the two different CQI feedback schemes, namely periodic mode or aperiodic mode. The eNodeB will create a trade-off between the best downlink adaptation, based on the CQI (considering the informed channel quality), and the overload on the uplink channel caused by the CQI itself, i.e., channel quality control traffic. There exists therefore a trade-off between downlink adaptation and uplink overload. LTE specifications are designed to provide the needed indicators for interoperability between eNodeB and UE, enabling the eNodeB to optimize link adaptation. The method that the eNodeB will use to explore available information is not standardized and as such left up to the manufacturer. In general, in response to CQI feedback, the eNodeB can choose between different modulation schemes (QPSK, 16-QAM and 64-QAM) and a wide range of code rates.

The ideal switching point between the different modulation combinations and the code rate depends on a series of factors that include the required Quality

of Service (QoS) and the cell throughput. The channel code scheme for FEC, which is the basis for the code rate adaptation mechanism, was the object of an in-depth study during the LTE standardization process. The channel coding theory has been intensely researched over the last decades, especially with the discovery of turbo codes, offering performance close to the Shannon limit and the development of general iterative processing techniques. More advanced channel coding resources were added, with the introduction of link adaptation, including Hybrid Automatic Repeat request (HARQ), a combination of ARQ and channel coding, improving robustness against channel fading. These schemes include incremental redundancy, by means of which the code rate is progressively reduced, transmitting additional parity information at each retransmission.

2.2.4 Uplink transmission

For LTE uplink transmission, the link adaptation process is similar to the downlink adaptation process, again with the eNodeB handling the selection of modulation and coding schemes (MCS). An identical channel coding structure is used for the uplink, while the modulation scheme can be either QPSK or 16-QAM, and for the maximum UE category, 64-QAM modulation is also available. The main difference between the uplink and downlink is that, instead of basing link adaptation on CQI feedback, the eNodeB can make its own estimate of the uplink data rate that the sounding channel can handle, e.g, by using Sounding Reference Signals (SRS). An important final aspect regarding link adaptation is its use for time and frequency scheduling of multiple users, which allows radio transmission resources to be efficiently shared among the users (since the channel capacity for individual users varies). CQI can therefore be used not only to adapt code rate and modulation in response to actual channel conditions, but for optimal time- frequency selective scheduling and for managing interference among the cells.