text: In this paper, we demonstrate the optimal power allocation for QPSK, 16-QAM, and 64-QAM modulation schedules and the role of channel quality indicator (CQI). We used sigmoidal-like utility functions to represent the probability of successful reception of packets at user equipment (UE). CQI as a feedback to the base station (BS) indicates the data rate that a downlink channel can support. With Levenberg-Marquardt (LM) Optimization method, we present utility functions of different CQI values for standardized 15 Modulation order and Coding Scheme (MCS) in @math Generation Partnership Project (3GPP). Finally, we simulate and show the results of the optimal power allocation algorithm.
  @cite_1: We apply coset codes to adaptive modulation in fading channels. Adaptive modulation is a powerful technique to improve the energy efficiency and increase the data rate over a fading channel. Coset codes are a natural choice to use with adaptive modulation since the channel coding and modulation designs are separable. Therefore, trellis and lattice codes designed for additive white Gaussian noise (AWGN) channels can be superimposed on adaptive modulation for fading channels, with the same approximate coding gains. We first describe the methodology for combining coset codes with a general class of adaptive modulation techniques. We then apply this methodology to a spectrally efficient adaptive M-ary quadrature amplitude modulation (MQAM) to obtain trellis-coded adaptive MQAM. We present analytical and simulation results for this design which show an effective coding gain of 3 dB relative to uncoded adaptive MQAM for a simple four-state trellis code, and an effective 3.6-dB coding gain for an eight-state trellis code. More complex trellis codes are shown to achieve higher gains. We also compare the performance of trellis-coded adaptive MQAM to that of coded modulation with built-in time diversity and fixed-rate modulation. The adaptive method exhibits a power savings of up to 20 dB.
  @cite_7: Abstract In this paper, we introduce a novel approach for power allocation in cellular networks. In our model, we use sigmoidal-like utility functions to represent different users’ modulation schemes. Each utility function is a representation of the probability of successfully transmitted packets per unit of power consumed by a user, when using a certain modulation scheme. We consider power allocation with utility proportional fairness policy, where the fairness among users is in utility percentage i.e. percentage of successfully transmitted packets of the corresponding modulation scheme. We formulate our power allocation optimization problem as a product of utilities of all users and prove that it is convex and therefore the optimal solution is tractable. We present a distributed algorithm to allocate base station powers optimally with priority given to users running lower modulation schemes while ensuring non-zero power allocation to users running higher modulation schemes. Our algorithm prevents fluctuation in the power allocation process and is capable of traffic and modulation dependent pricing policy. This can be used to flatten traffic and decrease the service price for users. We also compare our results with a benchmark algorithm and show that our algorithm performs better in allocating powers fairly to all users without dropping any user in order to maximize performance.
  @cite_3: In this paper, we investigate resource block (RB) assignment and modulation-and-coding scheme (MCS) selection to maximize downlink throughput of long-term evolution (LTE) systems, where all RB's assigned to the same user in any given transmission time interval (TTI) must use the same MCS. We develop several effective MCS selection schemes by using the effective packet-level SINR based on exponential effective SINR mapping (EESM), arithmetic mean, geometric mean, and harmonic mean. From both analysis and simulation results, we show that the system throughput of all the proposed schemes are better than that of the scheme in [7]. Furthermore, the MCS selection scheme using harmonic mean based effective packet-level SINR almost reaches the optimal performance and significantly outperforms the other proposed schemes.
  @cite_17: We propose an optimal modulation and coding scheme (MCS) selection criterion for maximizing user throughput in cellular networks. The proposed criterion adopts both the Chase combining and incremental redundancy based hybrid automatic repeat request (HARQ) mechanisms and it selects an MCS level that maximizes the expected throughput which is estimated by considering both the number of transmissions and successful decoding probability in HARQ operation. We also prove that the conventional MCS selection rule is not optimized with mathematical analysis. Through link-level and system-level simulations, we show that the proposed MCS selection criterion yields higher average cell throughput than the conventional MCS selection schemes for slowly varying channels.
summary: The MCS selection has been widely studied. Work in @cite_1 - @cite_17 has proposed adaptive modulation and coding (AMC) to enhance the system throughput according to the channel quality. The CQI, the only feedback to BS, corresponds to a resource block (RB) or multiple RB's in the form of MCS index @cite_3 . And CQI value provides important information in link adaption. The study in @cite_3 developed several MCS selection schemes for downlink transmission in LTE systems by using the effective packed-level SINR. Thresholds were set to the SINR values with the Block Error Rate (BLER) smaller than 10 This paper is organized as follows. We first introduce the system model set up in Section . Then we review the CQI with more details in Section . In Section , we describe the solution for mapping the CQI values to the utility function. Section that briefly describes the optimal power allocation algorithm that was proposed in @cite_7 . In Section , we discuss the simulation set up and the results along with a discussion. Finally, Section concludes this paper.