Top PDF Multiple-Input Multiple-Output Detection Algorithms for Generalized Frequency Division Multiplexing

Multiple-Input Multiple-Output Detection Algorithms for Generalized Frequency Division Multiplexing

Multiple-Input Multiple-Output Detection Algorithms for Generalized Frequency Division Multiplexing

Since its invention, cellular communication has dramatically transformed personal lifes and the evolution of mobile networks is still ongoing. Evergrowing demand for higher data rates has driven development of 3G and 4G systems, but foreseen 5G requirements also address diverse characteristics such as low latency or massive connectivity. It is speculated that the 4G plain cyclic prefix (CP)-orthogonal frequency division multiplexing (OFDM) cannot sufficiently fulfill all requirements and hence alternative waveforms have been in- vestigated, where generalized frequency division multiplexing (GFDM) is one popular option. An important aspect for any modern wireless communication system is the ap- plication of multi-antenna, i.e. MIMO techiques, as MIMO can deliver gains in terms of capacity, reliability and connectivity. Due to its channel-independent orthogonality, CP- OFDM straightforwardly supports broadband MIMO techniques, as the resulting inter- antenna interference (IAI) can readily be resolved. In this regard, CP-OFDM is unique among multicarrier waveforms. Other waveforms suffer from additional inter-carrier in- terference (ICI), inter-symbol interference (ISI) or both. This possibly 3-dimensional in- terference renders an optimal MIMO detection much more complex. In this thesis, we investigate how GFDM can support an efficient multiple-input multiple-output (MIMO) operation given its 3-dimensional interference structure. To this end, we first connect the mathematical theory of time-frequency analysis (TFA) with multicarrier waveforms in general, leading to theoretical insights into GFDM. Second, we show that the detec- tion problem can be seen as a detection problem on a large, banded linear model under Gaussian noise. Basing on this observation, we propose methods for applying both space- time code (STC) and spatial multiplexing techniques to GFDM. Subsequently, we propose methods to decode the transmitted signals and numerically and theoretically analyze
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Turbo equalization for multiple-input multiple-output (MIMO) wireless communication systems

Turbo equalization for multiple-input multiple-output (MIMO) wireless communication systems

A large number of low complexity SISO equalizers have been proposed to tradeoff the complexity with performance. A linear minimum mean squared error (MMSE) equalizer was proposed in [2]- [4] for turbo equalization, where the linear filter coefficients are calculated by using the a priori information at the equalizer input and are updated for each symbol. The complexity of the MMSE with time- varying coefficients can be reduced by using time-invariant coefficients for an entire block, at the cost of performance loss. One of the main performance limiting factors of MMSE is the residual interference at the output of the linear filter, especially for high level modulations. The residual interference of MMSE can be partly removed by means of decision feedback equalization (DFE) with either hard decisions [5] or soft decisions [6, 7]. Many of the DFE filter coefficients are derived by using the as- sumption of perfect interference cancelation, which is usually not the case in practical systems. In [8], a soft feedback equalizer (SFE) is developed without the assumption of perfect interference cancelation. Instead, the filter coefficients are developed by an- alyzing the statistical properties of the soft decisions and residual interference. The equalizer developed in [8] can only work for systems with binary modulations. It was later extended to system with high level modulations [9]. All the above works are developed for single-input single-output systems. Low complexity soft decision feedback equalizer (SDFE) [10] or reliability-based turbo detection [11] are proposed for MIMO systems, where the equalization needs to deal with both ISI and MI due to spatial multiplexing. All above works use time domain equalization. The complex- ity can be further reduced by employing single-carrier frequency domain equalization (SC-FDE) [12] and [13]. The low complexity of SC-FDE is usually achieved at the cost of performance loss due to the effects of noise enhancement [14] caused by fading compensation in the frequency domain during the FDE process.
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Orthogonal Frequency Division Multiplexing Based Air Interfaces and Multiple Input Multiple Output Techniques in Cooperative Satellite Communications for 4th Generation Mobile Systems

Orthogonal Frequency Division Multiplexing Based Air Interfaces and Multiple Input Multiple Output Techniques in Cooperative Satellite Communications for 4th Generation Mobile Systems

Current studies of future 4G mobile systems focus on the use of OFDM as a way of providing spectrum efficiency, along with high data rate transfer. OFDM has proven to be very effective in terrestrial networks, so its potential use over satellite transmissions would guarantee 4G systems capable of covering all geographical areas. OFDM splits a carrier with large bandwidth into multiple orthogonal sub-carriers of much smaller bandwidths. Cooperative Communications has also been intensively investigated by researchers as a way to transfer information from the source to the destination, using relay nodes when the end user is unreachable by the source. Cooperative Communication is a fairly recent concept and offers a reliable solution when a communication channel is unavailable in a network setting. This chapter puts forth a review of the topics that have already been investigated in OFDM, Cooperative Communications and the challenges of migration to 4G systems.
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Optimum low complexity filter bank for generalized orthogonal frequency division multiplexing

Optimum low complexity filter bank for generalized orthogonal frequency division multiplexing

As seen in Fig. 2, PR-QMF bank consists of synthesis filter bank as multiplexing part and analysis filter bank as de- multiplexing part. Connecting the output of the synthesis part directly to the input of the analysis part will completely reconstruct the original inputs of the filter bank. Further- more, in PR-QMF bank, synthesis filters are matched to corresponding analysis filters [14]. In addition, perfect re- construction property is preserved even when the convolu- tions are performed circularly, and thus, PR-QMF banks can also be classified as cyclic orthogonal filter banks [15]. Two-band PR-QMF banks are the simplest form of PR- QMF banks which are easily designed by using a prototype filter. Assume h(n) to be L-tap prototype filter-derived such that L is an even number and its Z transform satisfies the following condition:
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Improved multiple input multiple output blind equalization algorithms for medical implant communication

Improved multiple input multiple output blind equalization algorithms for medical implant communication

In order to achieve the detection and monitoring of chronic disease, the human body physiolog- ical signals, such as heart rhythm, blood glucose level, body temperature, blood pressure and etc, are always required to be observed for sufficient long period. In order to obtain the physiological signals, wired medical sensor has conventionally been used. However, the wired medical sensor is heavy and big equipment, and thereby it can restrict patient’s movement. Therefore, battery- operated wireless medical sensor, which is relatively small and light, is developed to perform the similar task. The wireless medical sensor is not solely a sensor, but also has been integrated with processor, memory and radio frequency communication technology [58]. Hence, for the non- emergency case, the wireless medical sensor allows the patient to be home monitored and is helpful to reduce the face-to-face consultation times [59, 60, 61]. In this case, the resources such as pa- tient’s time and hospital space can be saved. In general, wireless medical sensor can be divided into wearable sensor and implant sensor, which are located on-body and in-body, respectively.
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Low-complexity iterative receiver algorithms for multiple-input multiple-output underwater wireless communications

Low-complexity iterative receiver algorithms for multiple-input multiple-output underwater wireless communications

High data-rate multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications is very challenging due to severe inter-symbol interference, strong spa- tial correlation and fast channel variation. Currently, two classes of low-complexity transmission schemes are commonly used in high data-rate coherent UWA communi- cations: orthogonal frequency division multiplexing (OFDM) and singer carrier fre- quency domain equalization (SC-FDE) [1, 2]. The OFDM system divides the data stream into multiple parallel data streams, which are transmitted with orthogonal sub- carriers. Since the sub-channels can be treated as frequency flat fading channels, the (Fast Fourier Transform) FFT based receiver can be implemented with low complexity. SC-FDE transmits in wideband but converts the received signal into frequency domain via FFT, performs frequency domain equalization, and converts the equalized signal back to time domain via IFFT before detection. The SC-FDE has the same overall transceiver complexity as that of the OFDM.
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Generalized Schemes of Orthogonal Frequency Division Multiplexing with Index Modulation

Generalized Schemes of Orthogonal Frequency Division Multiplexing with Index Modulation

The ML detector is optimum in the detection of received symbols in OFDM-IM, as it considers all possible subblock realizations by examining for all possible subcarrier index combinations. However, in general, our proposed scheme has many more combinations than OFDM-IM, making ML detector generally impractical .According to [1], LLR detector is a practical choice to trade off between the detection precision and detection complexity. In this subsection, the upgraded LLR detector for OFDM-GIM1 is proposed. Our generalized scheme has a flexible Kr K for p bit input signal with various values in an OFDM subblock. The receiver knows the set K in advance for each received symbol.To detect the information, every possible Kr must be considered.
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Efficient low-complexity data detection for multiple-input multiple-output wireless communication systems

Efficient low-complexity data detection for multiple-input multiple-output wireless communication systems

In the small-scale MIMO scenario, we study turbo equalization schemes for multiple- input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) and multiple- input multiple-output single-carrier frequency division multiple access (MIMO SC-FDMA) systems. For the MIMO-OFDM system, we propose a soft-input soft-output sorted QR de- composition (SQRD) based turbo equalization scheme under imperfect channel estimation. We demonstrate the performance enhancement of the proposed scheme over the conven- tional minimum mean-square error (MMSE) based turbo equalization scheme in terms of system bit error rate (BER) and convergence performance. Furthermore, by jointly con- sidering channel estimation error and the a priori information from the channel decoder, we develop low-complexity turbo equalization schemes conditioned on channel estimate for MIMO systems. Our proposed methods generalize the expressions used for MMSE and MMSE-SQRD based turbo equalizers, where the existing methods can be viewed as spe- cial cases. In addition, we extend the SQRD-based soft interference cancelation scheme to MIMO SC-FDMA systems where a multi-user MIMO scenario is considered. We show an improved system BER performance of the proposed turbo detection scheme over the conventional MMSE-based detection scheme.
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Wavelet Packet Transform Modulation for Multiple Input Multiple Output Applications

Wavelet Packet Transform Modulation for Multiple Input Multiple Output Applications

An investigation into the wavelet packet transform (WPT) modulation scheme for Multiple Input Multiple Output (MIMO) band-limited systems is presented. The implementation involves using the WPT as the base multiplexing technology at baseband, instead of the traditional Fast Fourier Transform (FFT) common in Orthogonal Frequency Division Multiplexing (OFDM) systems. An investigation for a WPT-MIMO multicarrier system, using the Alamouti diversity technique, is presented. Results are consistent with those in the original Alamouti work. The scheme is then implemented for WPT-MIMO and FFT- MIMO cases with extended receiver diversity, namely 2 ×Nr MIMO systems, where Nr is the number of receiver elements. It is found that the diversity gain decreases with increasing receiver diversity and that WPT-MIMO systems can be more advantageous than FFT-based MIMO-OFDM systems.
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Multiple Input Multiple Output Antenna Design

Multiple Input Multiple Output Antenna Design

CDMA (code division multiple access), OFDM (orthogonal frequency division multiplexing) and UWB (ultra wide band) are the system which simulink with communication and DSP signal library with smart antennas for manifold transmits and receives system. Most third generation mobile communication systems are using CDMA as their modulation technique. Prior to the modern industry advanced, the most frequent UWB system implementation was impulse radio, where ultra-short baseband pulses were used with a diversity of modulation schemes to transfer data. Impulse radio has several benefit over OFDM, with its capacity to pass through materials and unravel multipath with route length variation on the order of a foot or less.
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Semi-blind Turbo Detection for Multiple-input Multiple-output Wireless Systems

Semi-blind Turbo Detection for Multiple-input Multiple-output Wireless Systems

In order to explain the spatial multiplexing gain in MIMO, consider a wireless system with N t transmit antennas and N r receive antennas. At the transmitter N t data streams are transmitted that mix together in the wireless channel as they use the same frequency spectrum. At the receiver, the objective is to estimate the mixing channel matrix (through training symbols) and to separate individual data streams. Assuming flat-fading channels, that is, each entry of the channel matrix is a scalar coefficient, the separation of data streams is possible only if each receive antenna sees a sufficiently different channel. A highly scattering environment resulting in rich multipath ensures that this condition is satisfied. The key point here is that unlike conventional single-input single-output (SISO) wireless systems where multipath rep- resents an impediment to accurate transmission, MIMO actually exploits multipath to maximize the data rate over a given transmission link. Spatial multiplexing in MIMO is somewhat similar to code-division multiple access (CDMA) transmission in which multiple users/streams share the same time/frequency channel upon transmis- sion and are recovered through their unique codes (signatures). The main difference is that in MIMO, unique spatial signatures of input streams exist naturally due to rich multipath, thus using available spectrum more efficiently.
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Adaptive relaying protocol multiple-input multiple-output orthogonal frequency division multiplexing systems

Adaptive relaying protocol multiple-input multiple-output orthogonal frequency division multiplexing systems

Distributed space frequency coding applied to hybrid relay selection to ob- tain full spatial and full data rate transmission is explored. Two strategies, single cluster and multiple clusters, are considered for the Alamouti code at the desti- nation by using a hybrid relay protocol. The power allocation with and without sub-carrier pairing is also investigated to mitigate the effect of multipath error propagation in frequency-selective channels.

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Adaptive relaying protocol multiple-input multiple-output orthogonal frequency division multiplexing systems

Adaptive relaying protocol multiple-input multiple-output orthogonal frequency division multiplexing systems

strategy to achieve CD known as repetition-based when the relays contribute on orthogonal channels. However, this can reduce the spectral efficiency to a great extent with high number of relays. Diverse strategies have been investigated to improve the spectral efficiency, such as cooperative beamforming [139], relay se- lection and distributed space time codes [14]. Among these strategies DSTCs is powerful technique due to it being able to provide full rate transmission in addition to high throughput. The main conclusion of [14] was that the spatial diversity is equal to the available relays in the system not just the number of decoding relays. The outage capacity in a high-SNR regime was analyzed. The authors in [140] derived the pairwise error probability (PEP) for DSTC using a single relay AF mode, while in [141] a large number of relays were considered. The construction of DSTC in [142] has been done by exploiting the broadcast nature of the wireless communication and the optimal maximum likelihood (ML) decoder was proposed. The authors in [143] considered a time-reversal STC for multi-hop cooperative AF and DF relaying communications to achieve spatial diversity over flat and frequency-selective fading channels. In order to exploit DSTC, each AF relay node in the system encodes the received signal from the previous hop and then forwards it to the next hop. Jing and Hassibi [144] derived diversity and coding gains for multiple DF relay utilizing linear dispersion (LD) space-time code. In [145], the STC has been done at the source by dividing the encoded data into two consecutive vectors, each of them N symbols in length. Then at each relay node, the received vector is multiplied by a unique signature vector. The symbol error rate (SER) was derived for a non-orthogonal AF (NAF) scheme. The authors in [146] investigated opportunistic DSTC (O-DSTC) with full and half duplex mode. The system cooperative diversity considered that consisted of two users using DF scheme, collaborating with each other in transmitting their data to the same receiver. An incremental relaying strategy based on DF scheme in conjunction with DSTC was investigated in [147] and the closed-form of PEP was derived. All the aforementioned techniques were considered narrowband applica- tions (systems) where the channels experience flat-fading.
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Robust frequency-domain turbo equalization for multiple-input multiple-output (MIMO) wireless communications

Robust frequency-domain turbo equalization for multiple-input multiple-output (MIMO) wireless communications

To mitigate ISI and Doppler effect, a variety of time-domain and frequency-domain equalizers combined with Doppler compensation methods have been investigated for UWA communications [5] - [17]. Time-domain decision feedback equalization (TD-DFE) with a second-order digital phase-locked loop (PLL) has been successfully applied in single-input single-output (SISO) [6], single-input multiple-output (SIMO) [5], and multiple-input multi- ple output (MIMO) [11] UWA communications. However, due to long channel length and fast time-varying fading, the TD-DFE with PLL is often unstable, difficult to converge to optimal coefficients, and computationally prohibitive for long delay spreads. In contrast, frequency- domain equalization (FDE) can provide lower complexity and better robustness in severe ISI and Doppler fading channels. The common FDE schemes, multicarrier [12], orthogonal frequency division multiplexing (OFDM), and single carrier FDE (SC-FDE), have recently been applied to UWA communications successfully with excellent performance tested in real-world undersea experiments. In particular, the OFDM technique [13,14] employs a two- step Doppler mitigation method to combat severe UWA channels; and the SC-FDE [15–17] utilizes a group-wise phase correction method to combat fast phase rotation in equalized symbols.
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New Detection Algorithms for Single Input Multiple Output Systems with Carrier Frequency Offset

New Detection Algorithms for Single Input Multiple Output Systems with Carrier Frequency Offset

The proposed algorithms are primarily derived for a two branch SIMO system with one transmit and two receive antenna, and are further extended for the general case of multiple m-receive antennas. The performance of these detection algorithms is analyzed using simulation and plotting BER against the SNR. The simulation is performed for 4, 16 and 64 QAM modulation schemes along with equal energy modu- lation schemes such as 4, 8 and 16 PSK. A performance comparison is made with the conventional forms of these detection techniques. It is shown that the proposed algo- rithms demonstrate significant improvement under the mismatch channel and CFO scenario. Simulation results also validate its capacity to deal with very high estima- tion errors and the performance is shown to improve with the increase of estimation error variance. Thus, it can be concluded that the detection algorithms proposed in this thesis are a novel approach for practical implementation.
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A multigigabit per second integrated multiple-input multiple-output VLC demonstrator

A multigigabit per second integrated multiple-input multiple-output VLC demonstrator

Though this increase in the spatial density may not directly translate into the similar increment in the data rate, this demonstration provides a platform to use the multiple LEDs chips within each luminaire of the commercial chip-on-board (COB) LED architecture of illumination devices for parallel data transmission iii) higher MIMO order: the previously reported high-speed MIMO-VLC system are limited to 4- parallel channels. In the work, we have improved the number of channel to nine, limited by available transceivers and iv) scalability: since the transceiver is manufactured in CMOS technology, the system is readily scalable. We have demonstrated that the same system can be scaled from 4- channel to 9-channel. Higher order MIMO system is feasible
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Joint Antenna Impedance and Channel Estimation in Multiple-input, Multiple-output Receivers.

Joint Antenna Impedance and Channel Estimation in Multiple-input, Multiple-output Receivers.

In this dissertation, we consider the problem of antenna impedance estimation at MIMO receivers. We first develop a hybrid estimation framework for joint estimation of chan- nel information and antenna impedance at single-input, single-output (SISO) receiver in Rayleigh fading channels. Based on observation of training sequences via synchronously switched load at the receiver, we derive the joint maximum a posteriori and maximum- likelihood (MAP/ML) estimators for channel and impedance over multiple packets. How- ever, this joint ML estimator is found inconsistent. We modify it to make it consistent, which improves channel estimation also.
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Polarization reconfigurable antennas for space limited multiple input multiple output system

Polarization reconfigurable antennas for space limited multiple input multiple output system

The capacity improvement in MIMO by using spatial diversity like spatial multiplexing, transmit diversity or receive diversity are subject to enough and availability of space [11]. Even though the spatial diversity are extremely potential to increase capacity through space-separated technique, but this technique is not suitable for space-limited MIMO applications such as mobile terminal, compact base station or portable access point due to space is not an advantage to be exploit [12]. Benefits of multiple channels are difficult to be obtained by using spatial diversity due to space limitation. In addition, a physically separation distance about half wavelength is required between two elements in order to have acceptable mutual coupling [13], which result in unsuitable for space-limited MIMO applications.
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Adaptive space time equalisation for multiple antenna assisted multiple input multiple output systems

Adaptive space time equalisation for multiple antenna assisted multiple input multiple output systems

This paper investigates an adaptive space-time equalisation (STE) assisted multiuser detection scheme for multiple-antenna aided multiuser systems. A minimum bit error rate (MBER) de- sign is compared with the standard minimum mean square error (MMSE) design. It is shown that the MBER design provides signif- icant performance enhancement, in terms of achievable system bit error rate, over the MMSE design for the multiple-antenna assisted multiple-input multiple-output communication scenario. Adaptive implementation of the MBER STE is realised using a stochastic gra- dient based least bit error rate algorithm, which is demonstrated to consistently outperform the adaptive least mean square based STE.
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MULTIPLE-INPUT MULTIPLE-OUTPUT WIRELESS SYSTEM DESIGNS WITH IMPERFECT CHANNEL KNOWLEDGE

MULTIPLE-INPUT MULTIPLE-OUTPUT WIRELESS SYSTEM DESIGNS WITH IMPERFECT CHANNEL KNOWLEDGE

As mentioned in Subsection 2.2.2, from the information-theoretic point of view, the multiple access channel (MAC, uplink) is better understood than the broadcast channel (BC, downlink), due to their differences in interference and cooperation [17, 31]. From the viewpoint of signal processing, the uplink is also easier to deal with than the down- link [82, 83, 88, 108]. Thus, the uplink–downlink duality is an important tool to sim- plify the downlink system design (see Subsections 2.2.2 and 2.2.3). To be specific, in a multiuser system with multiple antennas at the base station (BS) and with single-antenna users, under perfect channel knowledge, with the same sum power, the achievable signal- to-interference-plus-noise ratio (SINR) regions and normalized MSE regions for both links are the same, when noise variances are identical at all receivers [82, 94, 110]. Because of duality, beamforming problems in the downlink can be solved by forming and solving a dual uplink problem [82, 88, 108]. The same idea has been applied to the linear precoder- decoder designs when both the BS and mobile stations (MSs) are equipped with multiple antennas [47, 89], the scenario considered in this chapter.
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