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4G: LTE/LTE-Advanced for Mobile Broadband

TL;DR: In this article, the authors focus on LTE with full updates including LTE-Advanced to provide a complete picture of the LTE system, including the physical layer, access procedures, broadcast, relaying, spectrum and RF characteristics, and system performance.
Abstract: Based on the bestseller "3G Evolution - HSPA and LTE for mobile broadband" and reflecting the ongoing success of LTE throughout the world, this book focuses on LTE with full updates including LTE-Advanced to provide a complete picture of the LTE system. Overview and detailed explanations are given for the latest LTE standards for radio interface architecture, the physical layer, access procedures, broadcast, relaying, spectrum and RF characteristics, and system performance. Key technologies presented include multi-carrier transmission, advanced single-carrier transmission, advanced receivers, OFDM, MIMO and adaptive antenna solutions, advanced radio resource management and protocols, and different radio network architectures. Their role and use in the context of mobile broadband access in general is explained. Both a high-level overview and more detailed step-by-step explanations of the LTE/LTE-Advanced implementation are given. An overview of other related systems such as GSM/EDGE, HSPA, CDMA2000, and WIMAX is also provided. This book is a 'must-have' resource for engineers and other professionals in the telecommunications industry, working with cellular or wireless broadband technologies, giving an understanding of how to utilize the new technology in order to stay ahead of the competition. The authors of the book all work at Ericsson Research and have been deeply involved in 3G and 4G development and standardisation since the early days of 3G research. They are leading experts in the field and are today still actively contributing to the standardisation of LTE within 3GPP. Includes full details of the latest additions to the LTE Radio Access standards and technologies up to and including 3GPP Release 10Clear explanations of the role of the underlying technologies for LTE, including OFDM and MIMO Full coverage of LTE-Advanced, including LTE carrier aggregation, extended multi-antenna transmission, relaying functionality and heterogeneous deploymentsLTE radio interface architecture, physical layer, access procedures, MBMS, RF characteristics and system performance covered in detail
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Proceedings ArticleDOI
01 Sep 2017
TL;DR: The maximum drone density that can be thoroughly monitored and safely coordinated by a UTM system with LTE communication links is identified and it is concluded that future research has to focus on the mitigation of inter-cell interference so even a larger number of drones can get reliable access to all UTM services.
Abstract: The increasing availability of cheap and powerful drones for various applications is likely to cause a heavy usage of the very low level airspace in metropolitan areas with hundreds of simultaneously airborne drones per square kilometer in the near future. Certainly, the predicted large number of drones presents a major challenge to future UTM and especially to supporting communications systems. However, a robust and reliable communications system for drone-to-infrastructure communications is inevitably needed to grant all drones access to various services provided by UTM. In previous works, it has already been shown that commercial LTE networks are capable of providing connectivity to drones flying at low altitudes in principle. However, airborne drones which transmit data to the UTM infrastructure produce severe inter-cell interference since they have a strong line-of-sight connection to multiple LTE base stations at a time. Hence, we investigate further the suitability of the LTE uplink for drone-to-infrastructure communications in very low level airspace by LTE system-level simulations in this work. In particular, we identify the maximum drone density that can be thoroughly monitored and safely coordinated by a UTM system with LTE communication links. Our simulations show that an LTE system with 5 Mhz uplink bandwidth can support a message delivery ratio of more than 95% for drone densities of up to 200 drones per square kilometer assuming that all drones have to periodically transmit messages of 300 bytes at a rate of 10 Hz. It is concluded that future research has to focus on the mitigation of inter-cell interference so even a larger number of drones can get reliable access to all UTM services.

11 citations

01 Jan 2012
TL;DR: A study on the performance of a multi-hop relay network with half-duplex relay with two scenarios is proposed, where the impact velocity on the latency time and system capacity is explained.
Abstract: Relay stations are usually used to improve the signal strength for users near a cell edge, thus extending cell coverage. This paper proposes a study on the performance of a multi-hop relay network. This work introduces half-duplex relay with two scenarios. The first scenario is that wherein the relay node (RN) acts to amplify and forward (AF) and decode and forward (DF), where the relay and user equipment (UE) are fixed. The second scenario is that wherein the proposed UE moves with angular velocity around RN, whereas RN moves with horizontal velocity toward the base station (BS) and UE. The performance measures of each scenario are represented, where the impact velocity on the latency time and system capacity is explained. Both simulation and analytical calculations are provided.

11 citations


Cites background from "4G: LTE/LTE-Advanced for Mobile Bro..."

  • ...Decode and forward (DF): DF relays detect the desired signal, encodes the signal, and forwards the new signal [3]....

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Journal ArticleDOI
TL;DR: The security analysis and simulation results verify that the proposed architectures are capable enough to protect long-term evolution backhaul traffic against various IP-based attacks.
Abstract: In this paper, we propose two secure virtual private network architectures for the long-term evolution backhaul network. They are layer 3 Internet protocol (IP) security virtual private network architectures based on Internet key exchange version 2 mobility and multihoming protocol and host identity protocol. Both architectures satisfy a complete set of 3GPP backhaul security requirements such as authentication, authorization, payload encryption, privacy protection, and IP-based attack prevention. The security analysis and simulation results verify that the proposed architectures are capable enough to protect long-term evolution backhaul traffic against various IP-based attacks. Copyright © 2016 John Wiley & Sons, Ltd.

11 citations

Proceedings ArticleDOI
01 May 2017
TL;DR: In the heavy traffic scenario, the proposed resource scheduling scheme based on feed-back for uplink SCMA grant-free transmission has a better packet drop performance than the pre-existing scheme.
Abstract: Sparse code multiple access (SCMA) is a novel air-interface technology proposed for the fifth generation (5G) mobile communication system. SCMA aims for energy saving, low latency and massive connectivity to satisfy 5G demand. SCMA grant-free transmission has been proposed to ensure low latency and massive connectivity. In this paper, the connection and packets drop performance of SCMA and OFDMA through a pre-existing resource scheduling scheme for uplink grant-free transmission are analyzed. When UEs are erratically required to transmit a great number of packets continuously, the packet loss rate is too high, which is a problem of the pre-existing scheme. Hence, a resource scheduling scheme based on feed-back for uplink SCMA grant-free transmission is proposed to solve this problem. The simulation results demonstrate that SCMA has a lower packet loss rate than OFDMA with the same resources and UEs. In the heavy traffic scenario, the proposed resource scheduling scheme based on feed-back has a better packet drop performance than the pre-existing scheme.

11 citations


Cites background from "4G: LTE/LTE-Advanced for Mobile Bro..."

  • ...However, SR can only be sent periodically resulting in ten odd or longer transmission latency [5]....

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01 Jan 2016
TL;DR: This thesis seeks to develop a robust semi-analytical performance prediction method for an advanced iterative receiver that processes spatially multiplexed signals that have propagated through frequency-selective receive correlated multiple-input multiple-output (MIMO) wireless communication channels.
Abstract: This thesis seeks to develop a robust semi-analytical performance prediction method for an advanced iterative receiver that processes spatially multiplexed signals that have propagated through frequency-selective receive correlated multiple-input multiple-output (MIMO) wireless communication channels. In a change of perspective, the proposed performance prediction methods are applied at the transmitter, which seeks to attain a target frame error rate (FER) either by adaptive power control or by adaptive modulation and coding (AMC). The performance prediction scheme utilises the statistical properties of the channel – namely noise variance, number of separable propagation paths and the eigenvalues of the receive correlation matrix – to predict the signal-to-interference-plus-noise ratio (SINR) at the output of a frequency domain soft interference cancellation minimum mean square error equaliser. The SINR distribution is used to derive the distribution of the variance of the log-likelihood ratios (LLRs) at the output of a soft symbol-to-bit demapper. Mutual information transfer charts establish a bijective relationship between the variance of the LLRs and mutual information. A 3rd Generation Partnership Project compliant turbo code is assumed. Since the decoder operates independently from the channel, its extrinsic information transfer (EXIT) charts can be simulated in advance. By utilising the approximate LLR variance distribution of the demapped equaliser output, it is possible to evaluate the probability of an intersection between an equaliser chart associated with a random channel realisation and a fixed decoder chart. This probability provides the FER. Since the proposed performance prediction method does not require any instantaneous channel state information, it can be applied at the transmitter side as a robust link adaptation scheme. In adaptive transmission power control, the modulation order and code rate are fixed. By iteratively adjusting transmission power, the transmitter attempts to find an equaliser output LLR variance distribution that reaches a specified target FER. In AMC, transmission power is fixed. The equaliser output's LLR variance distribution is determined by the modulation order, while the decoder chart's position is determined by the code rate. The transmitter iteratively adjusts the code rate and attempts to find a modulation order and code rate pairing that reaches the target FER. For vertically encoded spatially multiplexed systems, the adaptive transmission power control and AMC schemes are complemented by adaptive repeat redundancy and incremental redundancy hybrid automatic repeat request (HARQ) techniques, respectively.

11 citations


Cites background from "4G: LTE/LTE-Advanced for Mobile Bro..."

  • ...7 8 Symbols and abbreviations ⊗ Kronecker product (·)H complex-conjugate transpose (·)T transpose 0N N × 1 vector of zeros 1N N × 1 vector of ones avg (·) mean value of the scalars in a vector b Nb × 1 bit vector b bit CN ( µ, σ2 ) complex Gaussian distribution with mean µ and variance σ2 circ {·} circulant matrix generator diag {·} diagonal matrix generator E {·} expected value F K × K unitary discrete Fourier transform matrix FT NTK × NTK block diagonal discrete Fourier transform matrix: a Kronecker product of F and a K × K identity matrix F−1 K × K unitary inverse discrete Fourier transform matrix F−1R NRK × NRK block diagonal inverse discrete Fourier transform matrix: a Kronecker product of F−1 and a K × K identity matrix fk1,k2 coefficient of the unitary discrete Fourier matrix f ik1,k2 coefficient of the unitary inverse discrete Fourier matrix fβ̂ ( β̂ ) PDF of the effective SINR of a SISO/SIMO channel or a vertically encoded MIMO transmission with respect to equaliser a priori information value Îapra fβ̂ j ( β̂ j ) PDF of the effective SINR for transmit antenna j in a horizontally encoded MIMO transmission with respect to equaliser a priori information vector Îapra fβ̂ j,k ( β̂ j,k ) PDF of the effective SINR for transmit antenna j at the kth frequency bin of a frequency-selective MIMO channel with respect to equaliser a priori information vector Îapra 9 fβ̂′j,k ( β̂′j,k ) PDF of the effective SINR for transmit antenna j at the kth frequency bin of a frequency-selective MIMO channel with respect to equaliser a priori information vector Îapra with ISI removed (interference is comprised of CAI and/or CCI) fβ̂k ( β̂k ) PDF of the effective SINR at the kth frequency bin of a frequencyselective SISO/SIMO channel with respect to equaliser a priori information value Îapra fσ̂2a ( σ̂2a ) PDF of the approximated post equalisation LLR variance for a SISO/SIMO channel or a vertically encoded MIMO transmission with respect to equaliser a priori information value Îapra fσ̂2a, j ( σ̂2a, j ) PDF of the approximated post equalisation LLR variance of the jth spatial stream with respect to equaliser a priori information vector Îapra F̃ER approximate FER for a SISO/SIMO system or a vertically encoded MIMO transmission F̃ER j approximate FER of the jth spatial stream for a horizontally encoded or an MU-MIMO transmission FERH upper limit for the FER of the weakest stream in the AMC scheme for horizontally encoded or MU-MIMO systems FERL lower limit of the target FER region defined for link adaptation FERU upper limit of the target FER region defined for link adaptation d global iteration index ĝ (·) equaliser mapping function from a priori to a posteriori information g̃ j (·) decoder mapping function from a priori to extrinsic information for the jth spatial stream gRc (·) mapping function from LLR variance to code rate H NRK × NTK time domain channel matrix comprised of circulant submatrices Hi, j K × K circulant time domain channel matrix between transmit antenna j and receive antenna i hi, j,l time domain channel coefficient of the lth propagation path between transmit antenna j and receive antenna i IK K × K identity matrix Îapoa NT × 1 vector of equaliser’s a posteriori mutual information Îapra NT × 1 vector of equaliser’s a priori mutual information Ia mutual information value 10 Îapra equaliser’s a priori information Îapoa, j equaliser’s a posteriori information for the jth spatial stream Îapropt a specific point on the equaliser’s mutual information transfer chart that is considered in link adaptation Ĩapra, j decoder’s a priori information for the jth spatial stream Ĩexta, j decoder’s extrinsic information for the jth spatial stream Ĩextopt a specific point on the decoder’s EXIT chart that is considered in link adaptation = (·) imaginary part i receive antenna index j transmit antenna index imaginary unit K length of the discrete and inverse discrete Fourier transforms K′ number of frequency domain channel coefficients that are used by the FD-SIC-MMSE equaliser when calculating the effective SINR across the frequency spectrum k frequency domain index L number of separable propagation paths l propagation path index L LLR vector Ldi decoder input LLR vector Ldo decoder output LLR vector Lei soft bit-to-symbol mapper (indirectly equaliser) input LLR vector Leo soft symbol-to-bit demapper (indirectly equaliser) output LLR vector Ln LLR value of the nth bit Ldi,w,dn the nth decoder input LLR value for the dth global iteration of the wth transmission of a packet (in RR-HARQ) Leo,u,Nd(w−u)+1n the nth symbol-to-bit demapper (indirectly equaliser) output LLR value from the uth version of the packet during the (w − 1)th retransmission and after its (Nd (w − u) + 1)th global iteration (in RR-HARQ) L̄eo,w,dn the nth symbol-to-bit demapper (indirectly equaliser) output LLR value for the dth global iteration of the wth transmission of a packet (in RR-HARQ) after deinterleaving and depuncturing M modulation order M j modulation order of the jth spatial stream 11 Mopt optimised modulation order for a SISO/SIMO system or a vertically encoded MIMO transmission Moptj optimised modulation order of the jth spatial stream in a horizontally encoded system M modulation alphabet M j modulation alphabet of the symbols transmitted from the jth antenna m Nakagami distribution’s shape parameter Nb number of bits Nd number of global (or outer) iterations NM modulation dependent multiplier that is used when the LLR variance is calculated from the SINR NR number of receive antennas Ns number of symbols NT number of transmit antennas NactT number of active antennas employed in adaptive transmission (N act T ≤ NT) N ( µ, σ2 ) real Gaussian distribution with mean µ and variance σ2 n bit/symbol index P NT × NT transmission power matrix P̆ NTK × NTK transmission power matrix: a Kronecker product of P and a K × K identity matrix P j transmission power of the jth antenna Pmax maximum total transmission power (normalised to 1) Pmax, j maximum transmission power of the jth antenna Popt optimised total transmission power for adaptive power control P(N act T ) opt, j optimised transmission power of the jth antenna for adaptive power control when NactT antennas transmit data P(w+1)RR adapted total transmission power for the wth RR-HARQ retransmission P(w+1)RR, j adapted transmission power for the jth antenna during the wth RRHARQ retransmission Ptot the summed transmission power of the NT antennas (normalised to 1) P j ( Îapra ) the probability that the equaliser and decoder graphs of the jth spatial stream intersect with a given equaliser a priori vector Îapra R NR × NR receive correlation matrix 12 R̆ NRK × NRK receive correlation matrix: a Kronecker product of R and a K × K identity matrix Rc code rate Rfbc optimal code rate based on receiver feedback RIR,wc code rate after the (w − 1)th IR transmission Rmaxc maximum code rate Rminc minimum (unpunctured) code rate Roptc optimal code rate for a SISO/SIMO or a vertically encoded MIMO transmission Rc, j code rate for the jth spatial stream in a horizontally encoded MIMO transmission Roptc, j optimal code rate for the jth spatial stream in a horizontally encoded MIMO transmission < (·) real part QminPopt minimum ratio of the power of the RR-HARQ retransmitted packets and the optimised power of the initial transmission Qmin Roptc minimum code rate decrease for IR-HARQ transmissions r NRK × 1 received signal vector r̄FD NRK × 1 frequency domain residual vector after soft interference cancellation s0 saddle point value t time domain index for discrete channel realisations tr {·} trace of a matrix w packet transmission index x NTK × 1 transmitted signal vector x̂ NTK × 1 symbol estimate vector at the equaliser output x̃ NTK × 1 symbol estimate vector constructed from the soft decoder outputs x j K × 1 signal vector transmitted from antenna j x̂ j K×1 symbol estimate vector of the jth transmit antenna at the equaliser output x̃ j K × 1 symbol estimate vector constructed from the soft decoder outputs corresponding to the symbols transmitted from antenna j ẋ j K × 1 vector containing the expected powers of the symbols transmitted from antenna j 13 ẍ j K × 1 vector containing the expected powers of the soft symbols calculated from the soft decoder outputs corresponding to transmit antenna j x j,k symbol transmitted from the jth antenna at the kth frequency bin x̂ j,k equaliser output soft estimate of the symbol transmitted from the jth antenna at the kth frequency bin x̃ j,k decoder output soft estimate of the symbol transmitted from the jth antenna at the kth frequency bin (constructed from the decoder’s output LLRs) α modulation symbol coordinate β j effective SINR at the output of the FD-SIC-MMSE equaliser for the jth transmit antenna β̂ effective SINR at the output of the FD-SIC-MMSE equaliser for a SISO/SIMO channel or a vertically encoded MIMO transmission with respect to a priori information value Îapra β̂ j effective SINR at the output of the FD-SIC-MMSE equaliser for the jth transmit antenna with respect to a priori information vector Îapra β̂ j,k effective SINR at the output of the FD-SIC-MMSE equaliser for the jth transmit antenna at the kth frequency bin with respect to a priori information vector Îapra β̂′j,k effective SINR at the output of the FD-SIC-MMSE equaliser for the jth transmit antenna at the kth frequency bin with respect to a priori information vector Îapra with ISI removed (interference is comprised of CAI and/or CCI) β̂k effective SINR at the output of the FD-SIC-MMSE equaliser for a SISO/SIMO channel or a vertically encoded MIMO system at the kth frequency bin with respect to a priori information value Îapra Γ (·) gamma function γ (·, ·) lower incomplete gamma function ∆ diagonal matrix containing the symbol-wise residual interference energy after soft interference cancellation ∆̂a diagonal residual interference energy matrix corresponding to streamwise a priori information ∆̂a,− j diagonal residual interference energy matrix corresponding to stream- wise a priori information with the jth column and row removed 14 ∆̂a residual interference energy coefficient corresponding to a particular level of a priori information ∆̂opt residual interference energy coefficient used in link adaptation design parameter used to ensure the openness of convergence tunnel between the equaliser and decoder mutual information transfer charts ̃1, j convergence tunnel gap requirement in the LLR variance domain for the jth spatial stream for Ĩexta, j → 1 and (horizontally encoded MIMO transmission) ̃a convergence tunnel gap requirement in the LLR variance domain for Ĩexta and (SISO/SIMO or vertically encoded MIMO transmission) ̃a, j convergence tunnel gap requirement in the LLR variance domain for the jth spatial stream for Ĩexta, j and (horizontally encoded MIMO transmission) ̃opt convergence tunnel gap requirement in the LLR variance domain used in link adaptation for Ĩextopt and (SISO/SIMO or vertically encoded MIMO transmission) ζ ratio of transmit and receive antennas when NR → ∞ ζNR ratio of transmit and receive antennas when NR is finite η NRK × 1 zero-mean Gaussian noise vector with covariance matrix σ2ηINRK ηa Nb × 1 zero-mean Gaussian noise vector with covariance matrix σ2a INb θ gamma-distributed sum of squared absolute values of SIMO channel coefficients at a particular frequency bin (a squared absolute value of a channel coefficient for SISO channels) λRi ith eigenvalue of a receive correlation matrix λWj jth eigenvalue of a complex Wishart matrix µ|x̃|2 mean of the squared absolute values of soft symbol vector x̃ ξ vector of the impulse response’s average amplitudes ξl average amplitude of the impulse response of the lth propagation path ρ receive correlation coefficient Σr̄FD NRK × NRK covariance matrix of the frequency domain residual vector after soft interference cancellation σ2a LLR variance σ2|x̃|2 variance of the squared absolute values of soft symbol vector x̃ σ2η noise variance 15 σ̂20 LLR variance at the equaliser output corresponding to Î apr a = 0 (SISO/SIMO or vertically encoded MIMO transmission) σ̂20, j LLR variance at the equaliser output corresponding to Î apr a, j = 0 for the jth spatial stream (horizontally encoded MIMO transmission) σ̂2a LLR variance at the equaliser output corresponding to Î apr a (SISO/SIMO or vertically encoded MIMO transmission) σ̂2a, j LLR variance at the equaliser output corresponding to Î apr a, j for the jth spatial stream (horizontally encoded MIMO transmission) σ̂2a,RRw accumulated LLR variance after the wth transmission of a packet in RR-HARQ corresponding to Îapra (SISO/SIMO or vertically encoded MIMO transmission) σ̂2a,t (t) LLR variance at the intersection point of the equaliser and decoder mutual information transfer charts at a discrete time instant t (SISO/SIMO or vertically encoded MIMO transmission) σ̂2fb approximation of the LLR variance at the equaliser output after the first instance of equalisation (SISO/SIMO or vertically encoded MIMO transmission) σ̂2fb,w approximation of the LLR variance at the equaliser output after the first instance of equalisation for the wth transmission of the packet (SISO/SIMO or vertically encoded MIMO RR-HARQ transmission) σ̃21, j decoder LLR variance corresponding to Ĩ ext a, j → 1 for the jth spatial stream (horizontally encoded MIMO transmission) σ̃2a decoder LLR variance corresponding to Ĩ ext a (SISO/SIMO or vertically encoded MIMO transmission) σ̃2a, j decoder LLR variance corresponding to Ĩ ext a, j for the jth spatial stream (horizontally encoded MIMO transmission) σ̃2opt decoder LLR variance corresponding to Ĩ ext opt Φ NRK × NTK frequency domain channel matrix Φi, j K × K diagonal frequency domain channel matrix between transmit antenna j and receive antenna i Φ j NRK × K frequency domain channel matrix between transmit antenna j and the NR receive antennas φik,k frequency domain channel coefficient for the ith receive antenna at the kth frequency bin of a SISO/SIMO channel Ψk NR × NT channel matrix at the kth frequency bin 16 Ψ− j,k NR × (NT − 1) channel matrix at the kth frequency bin; Ψk with the jth column removed ψk, j NR × 1 vector containing the frequency domain channel coefficients between transmit antenna j and the NR receive antennas at the kth frequency bin Ω Nakagami distribution’s spread parameter 1G 1st generation 2G 2nd generation 3G 3rd generation 3GPP 3rd Generation Partnership Project 3GPP2 3rd Generation Partnership Project 2 4G 4th generation 5G 5th generation 8-PSK octal phase-shift keying ACK acknowledgement AMC adaptive modulation and coding AMPS Advanced Mobile Phone Service APP a posteriori probability ARQ automatic repeat request AWGN additive white Gaussian noise BCJR Bahl–Cocke–Jelinek–Raviv BER bit error rate BICM bit-interleaved coded modulation BPSK binary phase-shift keying CAI co-antenna interference CCI co-channel interference CDF cumulative distribution function CDMA code division multiple access CLT central limit theorem CP cyclic prefix CQI channel quality indicator CSI channel state information CSIT channel state information at the transmitter CSIR channel state information at the receiver 17 DFT discrete Fourier transform DS direct-sequence EDGE Enhanced Data rates for GSM Evolution EXIT extrinsic information transfer FD frequency domain FDD frequency division duplexing FDMA frequency division multiple access FEC forward error control FER frame error rate GSM Global System for Mobile communications GPRS General Packet Radio Service HARQ hybrid automatic repeat request HSPA High Speed Packet Access IBI inter-block interference IDFT inverse discrete Fourier transform IID independently and identically distributed IMT-A International Mobile Telecommunications-Advanced IR incremental redundancy ISI inter-symbol interference ITU International Telecommunication Union LA link adaptation LDPC low-density parity check LLR log-likelihood ratio LQM link quality metric LUT look-up table LTE Long Term Evolution LTE-A Long Term Evolution-Advanced MAI multiple access interference MAP maximum a posteriori MC Monte Carlo MCS modulation and coding scheme ML maximum likelihood MGF moment generating function MIMO multiple-input multiple-output MMSE minimum mean-square error 18 MSE mean-square error MU multi-user NMT Nordic Mobile Telephone NACK negative acknowledgement OFDM orthogonal frequency-division multiplexing OFDMA orthogonal frequency-division multiple access PAPR peak-to-average power ratio PDF probability density function PDP packet drop probability PSK phase-shift keying QAM quadrature amplitude modulation QPSK quaternary phase-shift keying RA repeat–accumulate RAN radio access network RR repetition redundancy RX receive SC single carrier SDMA space-division multiple access SF space–frequency SIC soft interference cancellation SIMO single-input multiple-output SINR signal-to-interference-plus-noise ratio SIR signal-to-interference ratio SISO single-input single-output SNR signal-to-noise ratio SU single user ST space–time TD time domain TDD time division duplexing TDMA time division multiple access TX transmit UMTS Universal Mobile Telecommunications System WCDMA Wideband Code Division Multiple Access WiMAX Worldwide Interoperability for Microwave Access ZF zero-forcing 19 20 Contents Abstract Tiivistelmä Preface 7 Symbols and abbreviations 9 Contents 21 1 Introduction 23 1.1 Evolution of cellular networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23 1.2 Broadband MIMO communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....

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  • ...Long Term Evolution-Advanced (LTE-A) [11] and IEEE 802.16m-2011 [12], also known as WirelessMAN-Advanced and mobile WiMAX Release 2, are referred to as “true” 4G....

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  • ...Long Term Evolution-Advanced (LTE-A) [11] and IEEE 802....

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