Long Term Evolution Downlink Research Articles

Two Dimensional Signal Spreading in UMTS LTE: Exploiting Time-Frequency Diversity to Increase Throughput

This paper proposes a two-dimensional spreading method in UMTS Long Term Evolution (LTE). Such a method brings additional time-frequency diversity which is beneficial in terms of the ability to decode transmitted data at the receiver site under multipath fading. Additional diversity is provided due to the fact that chips of transmitted signals are spread using a Walsh-Hadamard spreading sequence over several subcarriers as well as over several time-slots simultaneously. A comparison with state-of-the-art LTE downlink transmission is provided. To enable reproducibility and to increase credibility of our results, an open source Vienna LTE simulator is utilized. LTE transmissions with the proposed 2D spreading are tested on several channel models. Simulations show that apart from an Additive White Gaussian Noise channel model, this 2D spreading based method outperforms the throughput performance of standard LTE. At high Signal to Noise Ratio (SNR), the throughput increase in most channel models is higher than 10 %.

Application of syndrome based Turbo decoding with adaptive computational complexity in LTE downlink

Abstract. This paper describes the application of an adaptive complexity decoder for the Long Term Evolution (LTE) downlink Turbo code. The proposed decoding approach is based on the block syndrome decoding principle and enables adaptive reduction of decoding effort depending on current SNR and iteration number with negligible influence on decoding performance. Numerical results in context of LTE downlink using typical mobile channels are used to demonstrate the efficiency of the approach.

Comparison between Performances of Channel estimation Techniques for CP-LTE and ZP-LTE Downlink Systems

In this paper, we propose to evaluate the performance of channel estimation techniques for Long Term Evolution (LTE) Downlink systems based on Zero Padding technique (ZP) instead of Cyclic Prefixing (CP). LTE Downlink system is a multiuser system based on a MIMO-OFDMA technology. Usually, in OFDM systems, a guard interval is inserted in order to mitigate both inter-carrier interference (ICI) and inter-symbol interference (ISI). LTE Downlink systems are based on CP-OFDM technique which consists of a copy a last OFDM symbols inserted at the beginning of each transmitted OFDM symbol. Although this technique shows good performances, the CP-LTE system suffers from a power efficiency loss.With the number of present OFDM symbols in LTE Downlink radio frame, the bandwidth loss becomes more important. Instead of CP, we propose to evaluate the performance of ZP-LTE systems in order to avoid the power efficiency .In this paper, we interest to evaluate the performance of channel estimation techniques for the two LTE Downlink systems. Simulations results show that although ZP-LTE systems outperform CP-LTE Downlink systems in terms of power efficiency, the CP-LTE systems show better performance than ZP-LTE systems and especially for high SNR values. MATLAB Monte-Carlo simulations are used to evaluate the performance of LS, LMMSE and Lr-LMMSE estimators in terms of Mean Square Error (MSE) and Bit Error Rate (BER) for 2x2 LTE Downlink systems.

Channel quality-to-interference ratio quantization criterion for limited feedback beamforming in MIMO systems

The discrete Fourier transform (DFT)-based codebook is employed in this paper to quantize channel state information so that the amount of feedback can be reduced in the multiple input multiple output (MIMO) downlink of long term evolution (LTE) system. And a novel beamforming (BF) scheme based on the proposed channel quality-to-interference (QIR) quantizing criteria is developed, which uses only the index of the optimal codebook for the beamforming at the base station (BS), and dramatically reduces the amount of feedback. The proposed BF scheme jointly considers the influences of the quality of the quantized channels and the mutual interference among the sub-channels. The extensive simulation results verify that throughput of the proposed BF scheme is better than that of the random BF with a little feedback, and that of the eigen-beamforming even under low signal noise ratio (SNR) scenario.

Multiuser scheduling on the LTE downlink with meta-heuristic approaches

In this paper, the issue of multi-user radio resource scheduling on the downlink of a Long Term Evolution (LTE) cellular communication system is addressed. An optimization model has been proposed earlier, where radio resources for multiple users are jointly allocated at the air-interface. It has been shown that an optimal solution to such a problem may provide reasonable gain over a simply greedy approach. However, the complexity of such an optimal approach could be prohibitively high. By exploiting meta-heuristic methods such as Genetic Algorithm (GA) and Simulated Annealing (SA), the results in this paper show that significant reduction in complexity can be obtained while achieving near-optimal solutions.

Complex Support Vector Machine Regression for Robust Channel Estimation in Lte Downlink System

In this paper, the problem of channel estimation for LTE Downlink system in the environment of high mobility presenting non-Gaussian impulse noise interfering with reference signals is faced. The estimation of the frequency selective time varying multipath fading channel is performed by using a channel estimator based on a nonlinear complex Support Vector Machine Regression (SVR) which is applied to Long Term Evolution (LTE) downlink. The estimation algorithm makes use of the pilot signals to estimate the total frequency response of the highly selective fading multipath channel. Thus, the algorithm maps trained data into a high dimensional feature space and uses the structural risk minimization principle to carry out the regression estimation for the frequency response function of the fading channel. The obtained results show the effectiveness of the proposed method which has better performance than the conventional Least Squares (LS) and Decision Feedback methods to track the variations of the fading multipath channel.

Optimal Allocation of Radio Resource in Cellular LTE Downlink Based on Truncated Dynamic Programming under Uncertainty

In the Cellular Long-Term Evolution (LTE) downlink, the smallest radio resource unit a Scheduler can assign to a user is a Resource Block (RB). Each RB consists of twelve (12) adjacent Orthogonal Frequency Division Multiplexing (OFDM) sub-carriers with inter-subcarrier spacing of 15 kHz. Over the years, researchers have investigated the problem of radio resource allocation in cellular LTE downlink and have made useful contributions. In an earlier paper for example, we proposed a deterministic dynamic programming based technique for optimal allocation of RBs in the downlink of multiuser Cellular LTE System. We found that this proposed methodology optimally allocates RBs to users at every transmission instant, but the computational time associated with the allocation policy was high. In the current work, we propose a truncated dynamic programming based technique for efficient and optimal allocation of radio resource. This paper also addresses uncertainty emanating from users’ mobility within a Cell coverage area. The objective is to significantly reduce the computational time and dynamically select applicable modulation scheme (i.e., QPSK, 16QAM, or 64QAM) in response to users’ mobility. We compare the proposed scheme with the Fair allocation and the earlier proposed dynamic programming based techniques. It is shown that the proposed methodology is more efficient in allocating radio resource and has better performance than both the Fair Allocation and the deterministic dynamic programming based techniques.

Performance Evaluation of MIMO-OFDM Modeling for UMTS-Long Term Evolution Downlink System

As the demand for the Mobile Communication Services increase, the research towards high data rate for meeting higher demands also increases. This made the path for the evolution towards the fourth generation Mobile Communication named as E-UTRA/UTRAN Long Term Evolution (LTE) given by 3GPP. In this paper LTE downlink performance is analyzed. Synchronization Error which degrades the OFDM System Performance is reduced by Synchronization Algorithm. This technique is implemented in Multiple Input Multiple Output (MIMO) to boost the capacity of the channel for to achieve higher data rate.

Energy efficient coordinated radio resource management: a two player sequential game modelling for the long-term evolution downlink

Inter-cell interference (ICI) is a key limiting factor to the radio frequency (RF) energy performance of a multi-cell multi-user radio access network (RAN). The channel quality of the cell edge users is greatly impaired by ICI owing to the fact that cell edge users are furthest away from their serving base stations (BSs) and closest to the interfering BSs. Consequently the BS is compelled to allocate more physical resource blocks [PRBs (In LTE a PRB spans 12 sub-carriers each with a bandwidth of 15 kHz over a 0.5 ms time slot)] to the cell edge users in order to meet their quality-of-service (QoS) targets. The study proposes a novel ICI management technique that mitigates the effects of ICI through a sequential game play between cells in the E-UTRAN [Evolved Universal Mobile Telecommunications Systems (UMTS) terrestrial radio access network] based on the instantaneous cell offered load. The proposed technique is shown to produce greater user channel quality improvements of 4 dB greater than the state-of-the-art ICI management techniques. The channel quality improvements result in a utilisation of less PRBs, RF and radio head energy which translate to energy reduction gains of 34 and 45% at low- and high-offered loads, respectively. In addition the proposed scheme does not require a central processing entity such as a radio network controller and can be implemented in unplanned self-organising networks.

Throughput Performance of 2X2 MIMO LTE Downlink in a Spatial Correlation Based Microcellular Channel for Wireless Broadband Networks

Multiple Input Multiple Output (MIMO) technology is going to be a viable alternative for future generation wireless broadband services in order to meet the striving requirements for throughput and system robustness. In Long Term Evolution (LTE), MIMO technologies have been broadly used to get better downlink peak rate, cell coverage, as well as average cell throughput. In the present paper a 2x2 MIMO is taken as baseline configuration for a LTE downlink under a Microcellular propagation scenario considering a non physical correlation based channel with Poor and rich scattering environment. The throughput capacity of the downlink is obtained for poor and rich scattering environments. Besides, two vital aspects of MIMO technique viz Spatial Multiplexing (SM) and Transmit Diversity (TD) are investigated in order to see their effect on throughput of the system. The effect of parameters like Speed of mobile station, number of Multipath, Rician factor (K) on throughput of such systems is reported and discussed. The investigations reported in this paper helps in estimating the throughput capacity of LTE downlink under SM and TD mode.

Wavelet-based downlink scheduling and resource allocation for long-term evolution cellular systems

This study proposes the use of wavelet transform in long-term evolution (LTE) cellular systems. Mathematical expressions are derived to represent data rate in LTE downlink transmission based on Wavelet and Fourier Transforms. Furthermore, a comparison between these two systems is provided. Simulation results show the proposed orthogonal wavelet division multiplexing (OWDM) approach outperforms the traditional orthogonal frequency division multiplexing-based systems. The data rate can also be increased by the amount of CyclicPrefix/SymbolTime%, as there is no need for a channel prefix in an OWDM-based system.

Estimation of highly selective channels for downlink LTE systemby a robust neural network

In this paper we propose a robust channel estimator for the downlink of a Long Term Evolution (LTE) system using a highly selective neural network. This method uses the information provided by the reference signals to estimate the total frequency response of the channel in two phases. In the first phase, the proposed method learns to adapt to the channel variations, and in the second phase it predicts the channel parameters. The performance of the estimation method in terms of complexity and quality is confirmed by theoretical analysis and simulations in an LTE/OFDMA (Orthogonal Frequency-Division Multiple Access) transmission system. The performance of the proposed channel estimator is compared with those of least-square decision feedback and modified Wiener methods. The simulation results show that the proposed estimator performs better than the above estimators and it is more robust at high-speed mobility.

Packet-Scheduling Algorithm by the Ratio of Transmit Power to the Transmission Bits in 3GPP LTE Downlink

Packet scheduler plays the central role in determining the overall performance of the 3GPP long-term evolution (LTE) based on packet-switching operation. In this paper, a novel minimum transmit power-based (MP) packet-scheduling algorithm is proposed that can achieve power-efficient transmission to the UEs while providing both system throughput gain and fairness improvement. The proposed algorithm is based on a new scheduling metric focusing on the ratio of the transmit power per bit and allocates the physical resource block (PRB) to the UE that requires the least ratio of the transmit power per bit. Through computer simulation, the performance of the proposed MP packet-scheduling algorithm is compared with the conventional packet-scheduling algorithms by two primary criteria: fairness and throughput. The simulation results show that the proposed algorithm outperforms the conventional algorithms in terms of the fairness and throughput.

Comparison of Strategies for Signaling of Scheduling Assignments in Wireless OFDMA

This paper considers the transmission of scheduling information in orthogonal frequency-division multiple-access (OFDMA)-based cellular communication systems such as the Third-Generation Partnership Project (3GPP) long-term evolution (LTE). These systems provide efficient usage of radio resources by allowing users to be dynamically scheduled in both frequency and time. This requires considerable amounts of scheduling information to be sent to the users. This paper compares two basic transmission strategies: transmitting a separate scheduling message to each user versus broadcasting a joint scheduling message to all users. Different scheduling granularities are considered, as are different scheduling algorithms. The schemes are evaluated in the context of the LTE downlink using multiuser system simulations, assuming a full-buffer situation. The results show that separate transmission of the scheduling information requires a slightly lower overhead than joint broadcasting when proportional fair scheduling is employed and the users are spread out over the cell area. The results also indicate that the scheduling granularity standardized for LTE provides a good tradeoff between scheduling granularity and overhead.

Downlink Scheduling for Multiclass Traffic in LTE

We present a design of a complete and practical scheduler for the 3GPP Long Term Evolution (LTE) downlink by integrating recent results on resource allocation, fast computational algorithms, and scheduling. Our scheduler has low computational complexity. We define the computational architecture and describe the exact computations that need to be done at each time step (1 milliseconds). Our computational framework is very general, and can be used to implement a wide variety of scheduling rules. For LTE, we provide quantitative performance results for our scheduler for full buffer, streaming video (with loose delay constraints), and live video (with tight delay constraints). Simulations are performed by selectively abstracting the PHY layer, accurately modeling the MAC layer, and following established network evaluation methods. The numerical results demonstrate that queue- and channel-aware QoS schedulers can and should be used in an LTE downlink to offer QoS to a diverse mix of traffic, including delay-sensitive flows. Through these results and via theoretical analysis, we illustrate the various design tradeoffs that need to be made in the selection of a specific queue-and-channel-aware scheduling policy. Moreover, the numerical results show that in many scenarios strict prioritization across traffic classes is suboptimal.