Top PDF Lte Downlink Transmission Scheme

Lte Downlink Transmission Scheme

Lte Downlink Transmission Scheme

LTE(Long Term Evolution) is the combination of both (radio and core )network. Radio means radiation wireless transmission of electromagnetic energy through space.It carry the information such as sound by systematically (modulating)some property of the radiated waves.The radio equipment involved in communication system includes the transmitter and reciever.each antenna having appropriate terminal equipment such as microphone at the transmitter loud speaker in the case of voice communication system.Core network means is the central part of the telecommunication network that provides various services to customer who are connected by access network.Core is the backbone network provides paths for the exchange of information between different sub networks.LTE provides high Spectral Efficiency,high peak data rate ,short round trip time,frequency flexiliblity .lte follows the technologies such as Orthogonal frequency division multiplexing (OFDM),Multiple input and multiple output(MIMO), robust channel coding ,scheduling and link adaptation .LTE provides seamless service and multimode devices for the customers hence its technology evolved over the multiple releases which have led to improved data throughput,lower latencies and increasingly flexible configurations .
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Analysis and Simulation of LTE Downlink and Uplink Transceiver

Analysis and Simulation of LTE Downlink and Uplink Transceiver

LTE downlink transmission scheme is based on Orthogonal Frequency Division Multiple Access (OFDMA), while the uplink transmission is based on Single Carrier Frequency Division Multiple Access (SC-FDMA). The main drawback of OFDMA over SC–FDMA is its high Peak to Average Power Ratio (PAPR) [8]. OFDMA allocates individual users in the time and the frequency domain and its signal generation in the transmitter is based on the Inverse Fast Fourier Transform (IFFT) [6]. OFDMA converts the wide-band frequency selective channel into a set of many fading sub-channels, which enables optimum receivers to be implemented with reasonable complexity during MIMO transmission [9]. In the uplink, SC–FDMA is more power efficient than OFDMA due to its low PAPR, which leads to decrease in linearity requirements and enhances the efficiency of the power amplifiers of the User Equipment (UE) [7]. SC-FDMA is based on discrete Fourier transform (DFT)-precoded OFDMA [5]. Concerning uplink, LTE output power limits vary depending on the frequency band. The maximum TX power is 23 dBm [6].
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A Comprehensive Review of Modulation Techniques used in Long Term Evolution

A Comprehensive Review of Modulation Techniques used in Long Term Evolution

Singal, TL requirements of the International mobile Telecommunications-advanced (ImT- advanced) of ITu-r for the fourth generation of mobile technologies (4g) [1]. In wireless cellular communication all services are circuit switched and partially packed switched, so LTE is designed with a goal of evolving the radio access technology assuming that all services would be packet-switched. In order to support several system bandwidth configurations ranging from 1.4 mHz up to 20 mHz LTE has been designed as a highly flexible radio access technology. radio spectrum access is based on the Orthogonal Frequency Division multiplexing (OFDm) scheme. Single Carrier Frequency Division multiple access (SC- FDma) and OFDma are used in uplink and downlink directions.
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PERFORMANCE ANALYSIS OF DOWNLINK MIMO IN LTE TECHNOLOGY

PERFORMANCE ANALYSIS OF DOWNLINK MIMO IN LTE TECHNOLOGY

In the event of FDD operation, there are two bearer frequencies, one for uplink transmission (FUL) and one for downlink transmission (FDL). Amid each casing, there are subsequently 10 uplink subframes and 10 downlink subframes and uplink and downlink transmission can happen at the same time inside a frame [6].

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A downlink non orthogonal multiple access scheme having physical layer security

A downlink non orthogonal multiple access scheme having physical layer security

CSI: Channel state information - State of propagation path between the base station and user terminal; FFT: Fast Fourier transform - Signal processing technique used for the modulation and demodulation processing of OFDM, in addition to frequency analysis of signals such as images/sounds; IFFT: Inverse fast Fourier transform - Similar to FFT, signal processing technique used for the modulation and demodulation processing of OFDM, in addition to frequency analysis of signals such as images/sounds. IFFT is a signal processing operation opposite to FFT; GI: Guard interval - The interval inserted between the symbol to be transmitted and the symbol. Thus, the influence of interference between symbols can be reduced, and it is used in OFDM and OFMDA or the like; SINR: Signal-to-interference noise ratio - A ratio of power other than the desired signal such as power of the desired signal and noise and interference from other cells; MLSE: Maximum likelihood sequence estimation - Signal detection method based on maximum a posteriori probability. The calculation complexity becomes huge in exchange for high detection accuracy; PF: Proportional fairness - One of scheduling methods considering fairness among accommodated users, which is used when allocating subcarriers to users in the multiple access method; FTPC: Fractional transmit power control - A method of power allocation among users in NOMA transmission; MLD: Maximum likelihood detection - As with MLSE, signal detection method based on maximum a posteriori probability used in the MIMO scheme
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Downlink LTE System Performance Improvement by Using BCH Codes over LTE-MIMO Channel

Downlink LTE System Performance Improvement by Using BCH Codes over LTE-MIMO Channel

The main goal of fourth generation (4G) mobile communication is to deliver high-speed data transmission. This demands higher charge to improve the technology standards. The additional cost may lower the consumer's attraction. The standard of 4G mobile communication is known as Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (E-UTRAN), which was initiated by Third Generation Partnership Project (3GPP). Unlike third-generation (3G) standard that uses CDMA schemes, the LTE uplink transmission utilizes single carrier- frequency division multiple access (SC-FDMA) and orthogonal frequency division multiplexing (OFDM) intended for downlink [1].
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Downlink Scheduling and Rate Capping for LTE Advanced Carrier Aggregation

Downlink Scheduling and Rate Capping for LTE Advanced Carrier Aggregation

can only be achieved and controlled on a cell basis; therefore, this solution is capable of neither achieving nor controlling throughput fairness between CA UEs and non-CA UEs. Also, it shall be noted that in fact the scheduling for CA cannot be fully independent per cell because there are UE data rate limits which shall not be exceeded when allocating resources on multiple cells to a CA UE. Such data rate limits are, for example, the 3GPP defined peak data rate of a given UE category [11] or the amount of UE data available for transmission in the buf- fer.

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Buffer aware adaptive resource allocation scheme in LTE transmission systems

Buffer aware adaptive resource allocation scheme in LTE transmission systems

Resource allocation for finite buffer space has been dis- cussed in the literature related to the wireless network. The authors in [14] design a new LTE buffer aware sched- uler to opportunistically assign RBs for video streaming applications in order to maximize the average video qual- ity. In [15], the buffer occupancy based approach is pre- sented to achieve video rate adaptation, while in [16], a dynamic programming framework is applied to study the buffer vs. QoS tradeoff for wireless media streaming in a single user scenario. These papers cited above mainly focus on video traffic. But the eNB in the practical situ- ation schedules and transmits general data traffic besides video traffic.
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Performance Analysis for Linearly Precoded LTE Downlink Multiuser MIMO

Performance Analysis for Linearly Precoded LTE Downlink Multiuser MIMO

Copyright © 2011 Zihuai Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The average channel capacity and the SINR distribution for multiuser multiple input multiple output (MIMO) systems in combination with the base station based packet scheduler are analyzed in this paper. The packet scheduler is used to exploit the available multiuser diversity in all the three physical domains (i.e., space, time and frequency). The analysis model is based on the generalized 3GPP LTE downlink transmission for which two spatial division multiplexing (SDM) multiuser MIMO schemes are investigated: single user (SU) and multiuser (MU) MIMO schemes. The main contribution of this paper is the establishment of a mathematical model for the SINR distribution and the average channel capacity for multiuser SDM MIMO systems with frequency domain packet scheduler, which provides a theoretical reference for the future version of the LTE standard and a useful source of information for the practical implementation of the LTE systems.
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An Improved Overloading Scheme for Downlink CDMA

An Improved Overloading Scheme for Downlink CDMA

for α = 0 . 5, 0 . 75, and 1, respectively. In addition to this, im- proved O/O with α = 1 and 0.75 performs better than the upper bound for synchronous transmission for a number of users higher than 82 and 91, respectively. For α = 0 . 5, im- proved O/O almost achieves the upper bound for K = 100. Further, we note that the achievable SINR is only slightly less than the value corresponding to static R. This indicates that the statistical fluctuation of R has only a minor e ff ect on achievable SINR, which hence can be approximated by the simple expression (23). Alternatively, one can tabulate the maximum acceptable channel overload ( K max − N ) /N as a
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Emulating extreme velocities of mobile LTE receivers in the downlink

Emulating extreme velocities of mobile LTE receivers in the downlink

We have shown that time interpolating OFDM signals prior to their transmission followed by the correspond- ing decimation at the receiver is a suitable technique for inducing high-speed effects (mainly ICI) while actually measuring at much lower speeds. The key idea behind the proposed technique is that the ICI level experienced by the received signals after OFDM demodulation and before channel equalizer depends on the relative factor between subcarrier spacing and Doppler spread; thus, instead of changing the Doppler spread, one can change the subcar- rier spacing by the same factor to obtain the same results. The main advantage of the proposed technique is its fea- ture to offer experimental evaluation of OFDM-based wireless communication systems at very high velocities while conducting measurements at much lower speeds. The price to be paid is that the signal bandwidth is reduced proportionally to the time interpolation factor, and therefore, potential inaccuracies could arise due to the loss of frequency diversity. However, to combat this loss in diversity, we proposed to transmit different replicas of the interpolated signal to cover the same bandwidth as in the non-interpolated case.
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A Survey on Channel Estimation Algorithms for LTE Downlink Systems

A Survey on Channel Estimation Algorithms for LTE Downlink Systems

N{X(k)} into time-domain signal {x(n)}. Then the parallel data stream is converted back to the serial data and guard interval is inserted between successive OFDM symbols to avoid the Inter Symbol Interference (ISI). If a guard interval with no signal transmission is inserted then the ISI can be eliminated almost completely, but a sudden change of waveform contains higher spectral components, so they result in Inter Carrier Interference (ICI). To avoid the Inter Carrier Interference (ICI), a guard interval with cyclic prefix is generally used. A copy of the last part of the OFDM symbol is attached to its front is called a Cyclic Prefix (CP). The transmitted signal x f (n) will pass through the
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LTE Downlink Channel Estimation Using Music Algorithm

LTE Downlink Channel Estimation Using Music Algorithm

In modern world, requirement of high data rate communication has become inevitable. Applications such as streaming transmission, video images, and World Wide Web browsing require high speed data transmission with mobility. In order to fulfill these data requirements, the 3 rd Generation Partnership Project (3GPP) [1][2] introduced Long Term Evolution (LTE), to provide high speed data rate for mobile communication. The LTE system affords an important effective bit rate and allows increasing system capacity in terms of numbers of simultaneous calls per cell. In addition, it has a low latency compared to 3G/3G + networks. It offers a theoretical speed of 100 Mbits/ s in the Downlink and 50Mbits/s in the Uplink transmission. The LTE uses Orthogonal Frequency Division Modulation (OFDM) and Orthogonal Frequency Division Modulation multiple access technique (OFDMA) in the downlink transmission [3]. The OFDM provides the signal transmitted Robustness against the multipath effect and can improve the spectral efficiency of the system [4][5]. On the other hand, the implementation of MIMO system increases channel capacity and decreases the signal fading by sending the same information at the same time through multiple antennas [5]. The combination of these two powerful technologies (MIMO-OFDM) in the LTE system improving thus the spectral efficiency and throughput offered without increasing resources for base bands and power output. To best exploit the power of MIMO-OFDM technology, it is imperative to manage at best the estimation of the channel coefficients; this operation is ensured by the interpolation of pilots[3]. In an OFDM system, the transmitter modulates the message bit sequence into PSK/QAM symbols, performs IFFT on the symbols to convert them into time-domain signals, and sends them out through a (wireless) channel. The received signal is usually distorted by the channel
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Carrier Frequency Synchronization in OFDM-Downlink LTE Systems

Carrier Frequency Synchronization in OFDM-Downlink LTE Systems

A radio frames in an LTE downlink transmission have a duration of Tframe = 10 ms.Each frame consists of 10 sub frames of equal length. Each sub frame contains two consecutive slots of time duration T slot = 0.5 ms.The smallest scheduling unit is called one resource block which is a timefrequency grid of 12 subcarriers over N s = 7 OFDM symbols for the normal CP length and N s = 6 for the extended CP length. In the LTE downlink two kinds of signals can be utilized for synchronization at the receiver. Firstly, the dedicated synchronization signals, and secondly the cellspecific reference symbols.
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Performance with MIMO for the Downlink 3GPP LTE Cellular Systems

Performance with MIMO for the Downlink 3GPP LTE Cellular Systems

which consists of a single data stream transmitted over multiple paths spaced in time dimension to achieve orthogonality. At the receiver side, the data stream is recovered through diversity combining. MIMO matrix A approach performs best at poor wireless channel condition at the receiver end (due to its robustness in a low SINR value), therefore it effectively improves coverage at cell edge. Multipath in this case is used as an advantage by diversifying the signal path, and sends two copies of the signal using different routes. MIMO Matrix A is best deployed in suburban and rural environments where the SINR might be weaker at the cell edges. It is also applicable for higher speed mobility conditions, where the SINR might be reduced. In these scenarios MIMO Matrix A with a two antenna implementation can double the system link budget and significantly boosting the coverage area. The intent for MIMO Matrix A deployment is to overcome unfavorable wireless transmission condition. Figure 1 depicts MIMO matrix A configuration:
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A novel downlink semi persistent packet scheduling scheme for VoLTE traffic over heterogeneous wireless networks

A novel downlink semi persistent packet scheduling scheme for VoLTE traffic over heterogeneous wireless networks

The scheduling algorithms in the packet scheduler as- sign RBs based on one of the following methods: Channel-aware and QoS-unaware, channel-unaware, or channel-aware and QoS-aware strategies. The first scheduling strategy assigns RBs based on the wireless channel quality. The user equipment (UE) reports the channel quality to the base station by periodically send- ing Channel Quality Indicator (CQI) feedback. This scheduling strategy has many advantages, mainly the ability to cope with the rapid changes in wireless chan- nel quality in both time and frequency domains. How- ever, it also has its own drawbacks relevant to this work, being the lack of provision for fairness between different users and their application services. It assigns RBs to users with high CQIs, and this can starve other users near cell edges due to their low CQIs. Dynamic schedul- ing defined in LTE protocol stack layer 2 is an example of this scheduling strategy [6, 7]. Dynamic scheduling in- cludes large amount of control signaling which is limited by the number of available Physical Downlink Control Channels (PDCCHs). It can, therefore, decrease VoLTE capacity and, for this reason, would be unsuitable for scheduling voice packets. Persistent scheduling, defined in LTE protocol stack layer 3 is, on the other hand, an important example of the second strategy [8, 9]. Unlike dynamic scheduling, persistent scheduling works by scheduling voice packets on a fixed basis, so no control signaling is required for the PDDCHs for every trans- mission. However, persistent scheduling reserves system bandwidth until the end of the call. It restricts the sys- tem capacity by the maximum system delay allowed be- cause a number of retransmissions may be needed. This might increase voice end-to-end delay which makes it an unsuitable scheduling method for VoLTE. Persistent scheduling works without taking the channel quality (CQI feedback) into account and seems unrealistic for VoLTE scheduling. The situation for the first and second scheduling strategies can become even worse when more than one RAT is involved in the process. For all the above reasons, the design of an efficient and QoS-aware resource allocation scheduling scheme which can ad- dress the above issues and improve the network per- formance is crucial to better satisfy end users ’ experience based on the application requirements.
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Review on Effective Image Communication Models

Review on Effective Image Communication Models

The processing of image transmission over LTE network is explained by the different stages of the block diagram shown in figure 1. In first step the image is broken into the small data packets by various schemes and then various encoding scheme is applied. Encoding is followed by interleaving process and then different modulation techniques are applied to the encoded data. To transmit data IFFT (Inverse Fast Fourier Transform) is carried out to convert data signal from data domain into frequency domain. And finally is transmitted from the communication channel. At the receiver inverse process as that of transmitter are carried out to receive the original transmitted data. Quality of image is evaluated by measuring the SNR and PSNR. The different transmission stages are studied with details in following section (Kasban1 Mohsen H., et al., 2016).
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Multi Functional Antenna Array Assisted MC DS CDMA Using Downlink Preprocessing Based on Singular Value Decomposition

Multi Functional Antenna Array Assisted MC DS CDMA Using Downlink Preprocessing Based on Singular Value Decomposition

Abstract— In this contribution we propose and investigate a transmitter preprocessing scheme designed for downlink transmission in multicarrier direct-sequence code-division multiple-access (MC DS-CDMA) systems using multiple base-station antenna arrays, where each antenna ar- ray employs multiple array elements. The transmitter preprocessing scheme is derived based on the singular value decomposition (SVD). Our transmitter preprocessing design is capable of supporting a high number of MC DS-CDMA users, while maintaining a high diversity gain at a low detection complexity at the remote mobile stations (MSs). The characteristics of MC DS-CDMA using the proposed transmitter preprocessing scheme are discussed and the achievable bit-error-rate (BER) performance is investigated, when assuming that each subcarrier experiences flat Rayleigh fading. Our simulation results demonstrate that for a SVD-assisted MC DS-CDMA system using M distinct transmit antenna arrays and time (T)-domain spreading sequences of length N e
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Resource allocation for downlink coordinated multipoint (CoMP) in lte advanced

Resource allocation for downlink coordinated multipoint (CoMP) in lte advanced

In theory, downlink capacity scales linearly with the number of transmit and receive antennas. In practice, the number of transmit antenna at a BS is always limited. Thus, the BS needs to select a restricted number of users to serve in each multi-user multiple-input multiple-output (MU- MIMO) transmission. A user selection strategy must be judiciously devised, because the users are coupled and their achievable rates depend on the orthogonality of their instantaneous channel states. To search for the optimal user subset using brute-force approach is computationally exhaustive due to the massive number of possible user subset combinations. In order to reduce the computational complexity, various suboptimal user selection algorithms have been considered. Orthogonality based user selection (Chen, Lv, Jiang, & Wang, 2010; Gupta, Chaturvedi, & Member, 2014) have been shown to well approximate the optimal capacity at low computational complexity. The BS chooses the first user with the highest channel quality. Then, the next user that provides the best potential performance when grouped with those selected ones is selected. The procedure repeats until users are selected. Other suboptimal user selection algorithms were studied in (Cho, Kang, & Kim, 2012; Gupta et al., 2014; Kudo, Takatori, Murakami, & Mizoguchi, 2011; Seki, Takyu, & Umeda, 2010; Xie & Zhang, 2014) .
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Downlink interference minimization in cooperative cognitive LTE femtocell networks

Downlink interference minimization in cooperative cognitive LTE femtocell networks

interference to the coexisting licensed systems. In this paper, based on cognitive sensing, we propose a joint channel assignment and power allocation scheme, aiming to minimize the aggregate interference from multiple femtocells to the licensed users while satisfying the constraints of each femtocell’s capacity and power budget. It is believed that the cooperation among multiple femtocells is quite helpful in mitigating the interference considering the mobility of the licensed users. Specifically, Hungarian algorithm is involved in our scheme to address the co-tier femtocell interference issue. In order to illustrate our scheme more explicitly, we come up with the concepts of Physical Cluster and Virtual Cluster and synthetically apply the related algorithms to reduce the interference step by step. Finally, the performances of employed algorithms are evaluated and analyzed. Numerical results have validated that the proposed scheme is viable and effective in managing the femtocell interference.
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