Novel SNR Analysis for Adaptive Modulation and Coding in Generalized OFDM and Single Carrier Systems

In this paper, we propose a throughput optimization scheme for relay protocols based on Adaptive Modulation and Coding (AMC). The performance of relay protocols with the AMC scheme and show that relay protocols with the AMC scheme are capable of providing better average throughput at a lower Signal to Noise Ratio (SNR) level as compared to the conventional scheme with no AMC. We perform 3GPP Long Term Evolution-Advanced (LTE-A) parameters based simulations to prove the performance comparison of adaptive Modulation and Coding Scheme (MCS) relay protocols with non-adaptive MCS relay protocols. The simulation results of the proposed system with adaptive MCS prove that among the Amplify-and-Forward (AF), Decode-and-Forward (DF) and De-Modulate-and-Forward (DMF), the DMF protocol performs best, at a lower SNR value and higher average throughput.

In this paper, main single carrier (SC) and multicarrier (MC) systems with frequency domain equalization (FDE) are reviewed with the objective to identify key features of the evolution path of air interfaces towards 4G. In particular, this paper shows that the FFT/IFFT operation can be seen as the concatenation of two operations: S/P conversion and spreading. We show that the transmitter of an OFDMA system performs a S/P conversion and a multiplication with specific complex spreading codes. By replacing the orthogonal complex spreading codes of this equivalent OFDMA system, with traditional orthogonal spreading codes that are used in DS-CDMA systems, for instance Walsh-Hadamard codes, we achieve a novel multicode-CDMA system. The comparison of this novel SC transmission scheme with other SC and MC systems shows that the novel SC system has almost the same performance as OFDMA and also similar PAPR. On the other hand, it has a pretty different behavior wrt other SC systems such as IFDMA and DS-CDMA with FDE.

Cross-layer techniques represent efficient means to enhance throughput and increase the transmission reliability of wireless communication systems. In this paper, a cross-layer design of aggressive adaptive modulation and coding (A-AMC), truncated automatic repeat request (T-ARQ), and user scheduling is proposed for multiuser multiple-input-multiple-output (MIMO) maximal ratio combining (MRC) systems, where the impacts of feedback delay (FD) and limited feedback (LF) on channel state information (CSI) are also considered. The A-AMC and T-ARQ mechanism selects the appropriate modulation and coding schemes (MCSs) to achieve higher spectral efficiency while satisfying the service requirement on the packet loss rate (PLR), profiting from the feasibility of using different MCSs to retransmit a packet, which is destined to a scheduled user selected to exploit multiuser diversity and enhance the system's performance in terms of both transmission efficiency and fairness. The system's performance is evaluated in terms of the average PLR, average spectral efficiency (ASE), outage probability, and average packet delay, which are derived in closed form, considering transmissions over Rayleigh-fading channels. Numerical results and comparisons are provided and show that A-AMC combined with T-ARQ yields higher spectral efficiency than the conventional scheme based on adaptive modulation and coding (AMC), while keeping the achieved PLR closer to the system's requirement and reducing delay. Furthermore, the effects of the number of ARQ retransmissions, numbers of transmit and receive antennas, normalized FD, and cardinality of the beamforming weight vector codebook are studied and discussed.

We address the application of adaptive modulation and coding (AMC) for third-generation (3G) wireless systems. We propose a new method for selecting the appropriate modulation and coding scheme (MCS) according to the estimated channel condition. We take a statistical decision making approach to maximize the average throughput while maintaining an acceptable frame error rate (FER). We use a first-order finite-state Markov model to represent the average channel signal-to-noise ratio (SNR) in subsequent frames. The MCS is selected in each state of this Markov model (among the choices proposed in the 3G standards) to maximize the statistical average of the throughput in that state. Using this decision-making approach, we also propose a simplified Markov model with fewer parameters, which is suitable in systems where changes in the fading characteristics need to be accounted for in an adaptive fashion. Numerical results are presented showing that both of our models substantially outperform the conventional techniques that use threshold-based decision making.

In single carrier (SC) systems using a data-dependent superimposed training (DDST) scheme, the data-induced interference that occurs during channel estimation is eliminated, but at the expense of data distortion. This distortion causes a data identification problem (DIP), in which the data sequence cannot be uniquely identified at the receiver end. Accordingly, the present study proposes a precoding scheme which solves the DIP in SC systems using DDST. Five design criteria are derived for the precoding matrix in order to eliminate DIP, achieve frequency diversity, maintain a low peak-to-average power ratio (PAPR), and minimize the receiver complexity. In addition, a low-complexity detection method is proposed for reducing the search space of the detection process. The simulation results show that the proposed precoding scheme successfully eliminates the DIP in traditional DDST schemes while maintaining the same PAPR as that of the traditional SC systems based on DDST.

In this paper, we combine adaptive modulation and coding (AMC) with multiple input multiple output (MIMO) VBLAST multiplexing to improve the throughput performance of AMC in next generation mobile communication systems. In addition, we propose a system that adopts selection transmit diversity (STD) in the combined AMC-MIMO VBLAST system. The received signal-to-noise ratio (SNR) is improved by adopting STD techniques and an improved SNR increases a probability of selecting modulation and coding scheme (MCS) level that supports higher data rate. From the simulation results, the investigated MIMO-STD VBLAST system provides a throughput gain of 1Mbps compared with simply combined AMC-MIMO VBLAST system when the required SNR is 15dB. Also, the higher throughput is achieved by AMC-TD schemes and AMC-STTD scheme provides about 250kbps increase in throughput. And AMC-STD with 2 transmit antennas achieves about 420 kbps throughput improvement over the conventional AMC at 9dB SNR.

This paper presents the effect of joint modulation and coding scheme (MCS) selection on a turbo soft interference canceller (SIC) for OFDM-MIMO multiplexing using adaptive modulation and coding (AMC). We use a turbo SIC to detect signals by performing iterative interference cancellation using soft-symbol estimates based on the a posteriori log-likelihood ratio (LLR) at the Max-Log-MAP decoder output and linear minimum mean-square error (LMMSE)-based signal detection. Joint MCS section selects the best MCS combinations of all transmission streams so that the total throughput is maximized considering the residual interference from other streams for the turbo SIC. Computer simulations show that the joint MCS selection mitigates the decrease in throughput due to the large difference in the peak data rate between consecutive MCSs compared to independent MCS selection. Hence, we show that by using joint MCS selection, the total throughput with the number of MCSs of N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MCS</sub> = 8 becomes almost identical to that for N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MCS</sub> = 12 for 4-by-4 MIMO multiplexing using the turbo SIC.

Research on Threshold Adjustment Algorithm in Adaptive Modulation and Coding

With the development of the underwater acoustic (UWA) adaptive communication system, energy-efficient transmission has become a critical topic in underwater acoustic (UWA) communications. Due to the unique characteristics of the underwater environment, the transmitter node will almost always have outdated channel state information (CSI), which results in low energy efficiency. In this paper, we take full advantage of bidirectional links and propose an adaptive modulation and coding (AMC) scheme that aims to maximize the long-term energy efficiency of a single link by jointly scheduling the coding rate, modulation order, and transmission power. Considering the complexity characteristics of UWA channels, we proposed a bit error ratio (BER) estimation method based on deep neural networks (DNN). The proposed network could realize channel estimation, feature extraction, and BER estimation by using a fixed pilot of the feedback link. Then, we design a channel classification method based on the estimated BERs of the modulation and coding scheme (MCS) and further model the UWA channels as a finite-state Markov chain (FSMC) with an unknown transition probability. Thus, we formulate the AMC problem as a Markov Decision Process (MDP) and solve it through a reinforcement learning framework. Considering the large state-action pairs, a double deep Q-network (DDQN) based scheme is proposed. Simulation results demonstrate that the proposed AMC scheme outperforms the fixed MCS with a perfect channel information state, and achieves near-optimal energy efficiency.

This paper presents a performance model of a wireless network with one-antenna transmitter scheduling information towards a set of terminals in a time-division fashion. Each terminal is enabled with a multiple-antenna maximum ratio combining (MRC) receiver. The objective of this model is to evaluate the performance of adaptive modulation and coding (AMC) in Rayleigh fading channels under two assumptions: 1) correlation between antennas, and 2) user scheduling based on maximum channel gain. The model is useful for cross-layer design purposes, as it provides a relatively low-complex representation of the physical-layer. Closed-form expressions are here derived of correct packet reception probabilities for different modulation and coding schemes (MCSs) with different values of block error rate (BLER) and spectral efficiency. Analytic expressions are derived with the help of the theory of order statistics, which allows for the study of the statistics of channel-aware scheduling. The results indicate that correlation does not always reduce performance. At low signal-to-noise ratio (SNR), correlation can improve performance rather than reducing it. By contrast, at high SNR, correlation is shown to always reduce the performance of the receiver. This low-SNR behavior is less evident as the number of antennas increases and more evident when the number of users included in the scheduling process increases.

Long Term Evolution (LTE) network offers a high throughput with low latency that makes it the best choice for Evolved Multimedia Broadcast Multicast Service (E-MBMS). E-MBMS transmits data to all users simultaneously using the same channel and same Modulation and Coding Scheme (MCS) level. Each user experiences different channel condition, so an MCS level should be selected properly to satisfy all users. Typically, MCS level is selected on the basis of users' worst channel condition which results in wasting network resources. Since the E-MBMS performance directly depends on the selected MCS level, an efficient Adaptive Modulation and Coding (AMC) scheme is essentially needed. This paper introduces a new mechanism that uses the Standard Deviation (SD) of MCS level of E-MBMS user group operated on single cell mode to efficiently select its optimal MCS level. Simulation results show that the proposed mechanism increase the spectrum efficiency, throughput, and lower Packet Loss Ratio compared to the Worst User Channel Condition mechanism and Fixed Predefined MCS mechanism.

This paper presents the performance of outer-loop control for adaptive modulation and coding (AMC) using mutual information (MI) based mapping between the block error rate (BLER) and received signal-to-interference plus noise power ratio (SINR) in the multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) downlink employing maximum likelihood detection (MLD). In AMC, we generate a mapping table between the BLER and MI per bit in advance, which is computed from the received SINR, assuming typical channel conditions including the path model and fading maximum Doppler frequency. Then, in the proposed outer-loop control, the measured MI per bit value for selecting the best modulation and coding scheme (MCS) is adjusted so that the measured BLER after turbo decoding satisfies the prescribed target value. Computer simulation results show that the outer-loop control achieves almost the same throughput as that with a mapping table assuming channel conditions identical to those for the actual measurement, while achieving nearly the identical target BLER. Moreover, we show that the best step size, which provides nearly the maximum throughput, differs according to the change in the maximum Doppler frequency in contrast to the relative feedback delay of the AMC loop. Nevertheless, it is insensitive to the target BLER value and frequency-selectivity of a channel model.

We propose a new framework to analyze perfor- mance considering finite-length queuing and adaptive modulation and coding (AMC) for multi-user VoIP services in wireless communication systems. We formulate an uplink VoIP system as two-dimensional discrete-time Markov chain (DTMC) based on a Markov modulated Poisson process (MMPP) traffic model and MCS (modulation and coding scheme)-level set transition reflect- ing users' channel variations. We extend transition modeling of MCS-level for single-user to transition modeling of MCS-level set for multi-user. Throughout our DTMC formulation, we present various performance metrics, such as average queue-length, the average number of arrived and serviced packets, and packet dropping probability.

This paper addresses the design of energy efficient precoding/decoding strategies for multiple-input multiple-output cyclic prefixed single carrier (MIMO CP-SC) systems with frequency-domain equalization. We opt for eigenbeamforming in the frequency domain for spatial precoding and decoding. We show that eigenbeamforming leads to a simple yet effective maximization of the energy efficiency (EE) of the MIMO CP-SC link. Moreover, the associated power allocation relies on the combination of waterfilling among the spatial streams and a proper distribution of the per-stream allocated power among subcarriers. Numerical results show that, if we account for the efficiency of the high power amplifier (HPA) associated with the peak-to-average power ratio (PAPR), CP-SC can be more energy efficient than orthogonal frequency division multiplexing (OFDM) for moderate to high signal-to-noise (SNR) values.

Recently, a hybrid single carrier(SC) and multi-carrier (MC) system based on the 4-weighted fractional Fourier transform (4-WFRFT) was proposed. As this hybrid carrier (HC) system contains MC component, it inherits the problem of high peak to average power ratio (PAPR). In this paper, we investigate the clipping technique for PAPR reduction in HC system. By analysis and simulation, we show that clipping technique is a simple and efficient way to overcome the large PAPR in HC system at the price of increased bit error ratio (BER). Furthermore, a higher MC proportion in HC leads to a worse BER performance.