1,171 research outputs found
Indoor wireless communications and applications
Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter
Multiuser MIMO-OFDM for Next-Generation Wireless Systems
This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems
Waveforms for the Massive MIMO Downlink: Amplifier Efficiency, Distortion and Performance
In massive MIMO, most precoders result in downlink signals that suffer from
high PAR, independently of modulation order and whether single-carrier or OFDM
transmission is used. The high PAR lowers the power efficiency of the base
station amplifiers. To increase power efficiency, low-PAR precoders have been
proposed. In this article, we compare different transmission schemes for
massive MIMO in terms of the power consumed by the amplifiers. It is found that
(i) OFDM and single-carrier transmission have the same performance over a
hardened massive MIMO channel and (ii) when the higher amplifier power
efficiency of low-PAR precoding is taken into account, conventional and low-PAR
precoders lead to approximately the same power consumption. Since downlink
signals with low PAR allow for simpler and cheaper hardware, than signals with
high PAR, therefore, the results suggest that low-PAR precoding with either
single-carrier or OFDM transmission should be used in a massive MIMO base
station
SYNCHRONIZATION AND RESOURCE ALLOCATION IN DOWNLINK OFDM SYSTEMS
The next generation (4G) wireless systems are expected to provide
universal personal and multimedia communications with seamless connection
and very high rate transmissions and without regard to the users’ mobility and
location. OFDM technique is recognized as one of the leading candidates to
provide the wireless signalling for 4G systems. The major challenges in
downlink multiuser OFDM based 4G systems include the wireless channel, the
synchronization and radio resource management. Thus algorithms are required
to achieve accurate timing and frequency offset estimation and the efficient
utilization of radio resources such as subcarrier, bit and power allocation.
The objectives of the thesis are of two fields. Firstly, we presented the
frequency offset estimation algorithms for OFDM systems. Building our work
upon the classic single user OFDM architecture, we proposed two FFT-based
frequency offset estimation algorithms with low computational complexity.
The computer simulation results and comparisons show that the proposed
algorithms provide smaller error variance than previous well-known algorithm.
Secondly, we presented the resource allocation algorithms for OFDM
systems. Building our work upon the downlink multiuser OFDM architecture,
we aimed to minimize the total transmit power by exploiting the system
diversity through the management of subcarrier allocation, adaptive
modulation and power allocation. Particularly, we focused on the dynamic
resource allocation algorithms for multiuser OFDM system and multiuser
MIMO-OFDM system. For the multiuser OFDM system, we proposed a lowiv
complexity channel gain difference based subcarrier allocation algorithm. For
the multiuser MIMO-OFDM system, we proposed a unit-power based
subcarrier allocation algorithm. These proposed algorithms are all combined
with the optimal bit allocation algorithm to achieve the minimal total transmit
power. The numerical results and comparisons with various conventional nonadaptive
and adaptive algorithmic approaches are provided to show that the
proposed resource allocation algorithms improve the system efficiencies and
performance given that the Quality of Service (QoS) for each user is
guaranteed.
The simulation work of this project is based on hand written codes in the
platform of the MATLAB R2007b
Time Domain Signal Detection for MIMO OFDM
The MIMO techniques with OFDM is regarded as a promising solution for increasing data rates, for wireless access qualities of future wireless local area networks, fourth generation wireless communication systems, and for high capacity, as well as better performance. Hence as part of continued research, in this paper an attempt is made to carry out modelling, analysis, channel matrix estimation, synchronization and simulation of MIMO-OFDM system. A time domain signal detection algorithm can be based on Second Order Statistics (SOS) proposed for MIMO-OFDM system over frequency selective fading channels. In this algorithm, an equalizer is first inserted to reduce the MIMO channels to ones with channel length shorter than or equal to the Cyclic Prefix (CP) length. A system model in which the ith received OFDM block left shifted by j samples introduced. MIMO OFDM system model which uses the equalizer can be designed using SOS of the received signal vector to cancel the most of the Inter Symbol Interference (ISI). The transmitted signals are then detected from the equalizer output. In the proposed algorithm, only 2P (P transmitted antennas / users in the MIMO-OFDM system) columns of the channel matrix need to be estimated and channel length estimation is unnecessary, which is an advantage over an existing algorithms. In addition, the proposed algorithm is applicable for irrespective of whether the channel length is shorter than, equal to or longer than the CP length. Simulation results verify the effectiveness of the proposed algorithm and shows that it out performs the existing one in all cases
On the Capacity of the Wiener Phase-Noise Channel: Bounds and Capacity Achieving Distributions
In this paper, the capacity of the additive white Gaussian noise (AWGN)
channel, affected by time-varying Wiener phase noise is investigated. Tight
upper and lower bounds on the capacity of this channel are developed. The upper
bound is obtained by using the duality approach, and considering a specific
distribution over the output of the channel. In order to lower-bound the
capacity, first a family of capacity-achieving input distributions is found by
solving a functional optimization of the channel mutual information. Then,
lower bounds on the capacity are obtained by drawing samples from the proposed
distributions through Monte-Carlo simulations. The proposed capacity-achieving
input distributions are circularly symmetric, non-Gaussian, and the input
amplitudes are correlated over time. The evaluated capacity bounds are tight
for a wide range of signal-to-noise-ratio (SNR) values, and thus they can be
used to quantify the capacity. Specifically, the bounds follow the well-known
AWGN capacity curve at low SNR, while at high SNR, they coincide with the
high-SNR capacity result available in the literature for the phase-noise
channel.Comment: IEEE Transactions on Communications, 201
Space-time-frequency block codes for MIMO-OFDM in next generation wireless systems
In this thesis the use of space-frequency block codes (SFBC) and space-time-frequency block codes (STFBC) in wireless systems are investigated. A variety of SFBC and STFBC schemes are proposed for particular propagation scenarios and system settings where each has its own advantages and disadvantages. The objective is to pro-pose coding strategies with improved flexibility, feasibility and spectral efficiency,and reduce the decoding complexity in an MIMO-OFDM system. Firstly an efficient SFBC with improved system performance is proposed for MIMO-OFDM systems. The proposed SFBC incorporates the concept of matched rotation precoding (MRP) to achieve full transmit diversity and optimal system performance foran arbitrary numberoftransmitantennas,subcarrierinterval andsubcarriergrouping. The MRP is proposed to exploit the inherent rotation and repetition properties of SFBC, arising from the channel power delay profile, in order to fully capture both space and frequency diversity of SFBC in a MIMO-OFDM system. It is able to relax restrictions on subcarrier interval and subcarrier grouping, making it ideal for adaptive/time-varying systems or multiuser systems. The SFBC without an optimization process is unstable in terms of achievable system performance and diversity order, and also risks diversity loss within a specific propagation scenario. Such loss or risk is prominent while wireless propagation channel has a limited number of dominant paths, e.g. relatively close to transmitters or relatively flat topography. Hence in orderto improve the feasibility of SFBC in dynamic scenarios, the lower bound of the coding gain for MRP is derived. The SFBC with MRP is proposed for more practical scenarios when only partial channel power delay profile information is known at the transmit end, for example the wireless channel has dominant propagation paths. The proposed rate one MRP has a relatively simple optimization process that can be transformed into an explicit diagram and hence an optimal result can be derived intuitively without calculations. Next, a multi-rate transmission strategy is proposed for both SFBCand STFBC to balance the system performance and transmission rate. A variety of rate adaptive coding matrices are obtained by a simple truncation of the coding matrix, or by parameter optimization for coding matrices for a given transmission rate and constellation. Pro-posed strategy can easily and gradually adjust the achievable diversity order. As a result it is capable of achieving a relatively smooth balance between system performance and transmission rate in both SFBC and STFBC, without a significant change of coding structure or constellation size. Such tradeoff would be useful to maintain stable Quality of Service (QoS) for users by providing more scalability of achievable performance in a time-varying channel. Finally the decoding procedure of space-time block code (STBC), SFBCand STFBC is discussed. The decoding of all existing STBC/SFBC/STFBC is unified at first, in order to show a concise procedure and make fair comparisons. Then maximum likelihood decoding (MLD) and arbitrary sphere decoding (SD) can be adopted. To reduce the complexity of decoding further, a novel decoding method called compensation de-coding (CD) is presented for a given space-time-frequency coding scheme. By taking advantage of the simplicity of zero-forcing decoding (ZFD) we are able to calculate a compensation vector for the output of ZFD. After modification by utilizing the com-pensation vector, the BER performance can be improved significantly. The decoding procedure is relatively simple and is independent of the constellation size. The per-formance of the proposed decoding method is close to maximum-likelihood decoding for low to medium SNR. A low complexity detection scheme, classifier based decoding (CBD), is further proposed for MIMO systems incorporating spatial multiplexing. The CBD is a hybrid of an equalizer-based technique and an algorithmic search stage. Based on an error matrix and its probability density functions for different classes of error, a particular search region is selected for the algorithmic stage. As the probability of occurrence of error classes with larger search regions is small, overall complexity of the proposed technique remains low, whilst providing a significant improvement in the bit error rate performance
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