Approximate Gram-Matrix Interpolation for Wideband Massive MU-MIMO Systems

This thesis presents two original ontributions on orthogonal frequency division multiplexing (OFDM). The first is a thorough investigation of the error performance and channel capacity of asymmetrically clipped optical OFDM (ACO-OFDM). ACO-OFDM is a modulation scheme designed specifically for optical communications. The second concerns the use of multiple-input multiple-output (MIMO) OFDM in radio frequency (RF) systems. A new scheme which uses polynomial cancellation coding (PCC) OFDM with time offsets is proposed. This new scheme is robust to both carrier frequency offset (CFO) and channel estimation errors. OFDM has been used extensively to reduce the effect of dispersion in wired and wireless RF systems. Although dispersion is also a problem in optical wireless systems, OFDM has not until recently been considered for use in these. This is because optical wireless systems use intensity modulation (IM) and so the transmitted signals must be nonnegative and as a result conventional OFDM signals which are bipolar cannot be used directly. ACO-OFDM and DC biased optical OFDM (DCO-OFDM) are two non-negative forms of OFDM developed for optical systems. Both are robust to ISI but ACO-OFDM is in most cases much more power efficient. In this thesis results are presented for the performance of ACO-OFDM, DCO-OFDM and conventional optical modulation schemes such as on-off keying (OOK) and pulse position modulation (PPM) for both dispersive and non-dispersive channels. These show that ACO-OFDM is more tolerant to dispersion and requires less optical power than the other modulation schemes. To investigate the theoretical limits of an ACO-OFDM system, closed form analytical expressions for the channel capacity of ACO-OFDM are derived both for a flat channel and for representative dispersive optical wireless channels. The capacity of ACO-OFDM cannot be compared with the general case of an intensity modulated signal, because no general solution for this has yet been found. Instead the mutual information of an ACO-OFDM signal is calculated and compared with two other signal distributions: an exponential distribution and a clipped-Gaussian distribution. The combination of OFDM and MIMO has been used in several radio standards. However, MIMO OFDM systems like single-input single-output (SISO) OFDM systems are very sensitive to CFO. An improved MIMO PCC OFDM system is proposed in this thesis. In this system, the signals transmitted from different antennae have different time offsets. At the receiver, OFDM symbols are demodulated by using each of these time offsets in a matched detection window. This system shows better performance than a MIMO PCC OFDM system without time offsets in two cases: when there are channel estimation errors and in MIMO systems with more transmit antennae than receive antennae.

Light emitting diode (LED) nonlinearities have a significant impact on the performance of optical wireless (OW) communication systems based on orthogonal frequency division multiplexing (OFDM) modulation. In this paper, different techniques to compensate for the induced nonlinearity distortions are presented and analyzed. First, single-carrier frequency division multiple access (SC-FDMA) is proposed instead of OFDM for OW systems. In SC-FDMA, some of the major OFDM problems such as high peak-to-average power ratio are inherently resolved. It is shown that the performance of OW OFDM systems and their counterpart SC-FDMA systems are traded off for certain input signal powers and modulation orders. Second, OW OFDM systems with hard, soft, and turbo channel coding techniques are considered. It is reported that significant performance gains can be achieved through channel coding. Finally, a novel method to reduce signal clipping distortion through the use of iterative signal clipping (ISC) and multiple transmit LEDs is proposed. The ISC technique is based on iterative clipping of the time domain OFDM signal and transmission from a multiple LED transmitter. Transmit LEDs are synchronized, located close to each other, and placed to emit light in the same direction. Hence, the channel path gains from each LED to the receiver photodiode are similar. The received signals from the different LEDs add coherently at the receiver. Reported results demonstrate that the effect of distortion is eliminated or significantly reduced based on the considered number of transmit LEDs.

In this paper, a downlink wireless transmission scheme is proposed for roadside deployment. The scheme is based on orthogonal frequency-division multiplexing (OFDM) technology, and it also employs virtual multiple input multiple output (MIMO) to further improve system capacity. In the "virtual" MIMO scheme proposed in this paper, signals can be sent from two base stations (BS) to one user, which creates a virtual MIMO system that may offer additional capacity gains in fading channels. This scheme is especially fit for the bi-sectional BSs with zonal coverage along roadside. Simulation results show that the proposed scheme can support both high and low speed users on road, and achieve a high system capacity gain especially in the cell edge. Within this scheme, the OFDM symbols are characterized into two groups: localized resource group (LRG), which is continuous in time-frequency (TF) domain; and distributed resource group (DRG) which is TF discrete. As LRG is fit for low-speed users to utilize the slowly varying channel while DRG is fit for high-speed users with rapid varying channels, the combination of them makes the allocation of OFDM subchannel more elastic to support users with different speed

We investigate an orthogonal frequency-division multiplexing (OFDM)-based downlink transmission scheme for large-scale multi-user (MU) multiple-input multiple-output (MIMO) wireless systems. The use of OFDM causes a high peak-to-average (power) ratio (PAR), which necessitates expensive and power-inefficient radio-frequency (RF) components at the base station. In this paper, we present a novel downlink transmission scheme, which exploits the massive degrees-of-freedom available in large-scale MU-MIMO-OFDM systems to achieve low PAR. Specifically, we propose to jointly perform MU precoding, OFDM modulation, and PAR reduction by solving a convex optimization problem. We develop a corresponding fast iterative truncation algorithm (FITRA) and show numerical results to demonstrate tremendous PAR-reduction capabilities. The significantly reduced linearity requirements eventually enable the use of low-cost RF components for the large-scale MU-MIMO-OFDM downlink.

Base station (BS) architectures for massive multi-user (MU) multiple-input multiple-output (MIMO) wireless systems are equipped with hundreds of antennas to serve tens of users on the same time-frequency channel. The immense number of BS antennas incurs high system costs, power, and interconnect bandwidth. To circumvent these obstacles, sophisticated MU precoding algorithms that enable the use of 1-bit DACs have been proposed. Many of these precoders feature parameters that are, traditionally, tuned manually to optimize their performance. We propose to use deep-learning tools to automatically tune such 1-bit precoders. Specifically, we optimize the biConvex 1-bit PrecOding (C2PO) algorithm using neural networks. Compared to the original C2PO algorithm, our neural-network optimized (NNO-)C2PO achieves the same error-rate performance at $\bf 2\boldsymbol\times$ lower complexity. Moreover, by training NNO-C2PO for different channel models, we show that 1-bit precoding can be made robust to vastly changing propagation conditions.

Multiple-input multiple-output (MIMO) wireless communication systems can achieve higher throughput through interference alignment. For a small number of users, determining the maximum possible degrees of freedom as well as the feasibility of interference alignment in MIMO systems is well studied. However, the issues of scheduling in systems employing interference alignment and serving a large number of users have received little attention so far. In this paper, we study the problem of joint scheduling, interference alignment, and packet admission control in MIMO wireless systems with the goal of maximizing system throughput subject to stability constraints. We formulate a stochastic network optimization problem and propose a scheduling and interference alignment (SIA) algorithm. In each time slot, SIA schedules some users among many competing ones to transmit data, and determines encoding and decoding matrices for the selected users. Packet admission control is performed in each time slot. In addition, we propose a heuristic semi-distributed algorithm (SDSIA), which has a lower computational complexity than the SIA algorithm. Via simulation, we evaluate the performance of SIA and SDSIA for different algorithm parameters and different numbers of users. We also compare the performance of SDSIA with other approaches which do not simultaneously exploit interference alignment and scheduling and find that the combination of these two techniques increases the achievable data rate dramatically.

Direction Finding of rogue Wi-Fi access points using an off-the-shelf MIMO–OFDM receiver

Wireless network is one of the most important things in the development of telecommunication. However, the existing wireless technology has not been able to efficiently create a very high data rate because it was very sensitive to fading. Therefore, Orthogonal Frequency Division Multiplexing (OFDM) technology combined with MIMO (Multiple Input Multiple Output) transceiver system was used to gain more diversity and bandwidth efficiency. The propagation performed on the OFDM MIMO system was multipath propagation. To reduce Intersymbol Interference (ISI) was used Zero Forcing (ZF) equalizer which works by combining channel response and equalizer response itself to eliminate ISI. This study aims to determine the effect of Zero Forcing Equalizer on OFDM MIMO system using rayleigh fading channel and compared the result with OFDM MIMO STBC system. The research method used was simulation using MatLab R2015a. The simulation results showed that the performance of OFDM MIMO ZF system was worse than OFDM MIMO STBC system i.e BER vs EbNo simulation, eye diagram simulation, and constellation diagram simulation. The OFDM MIMO ZF system was required an Eb / No value more than 25 dB to achieve BER 10-4 while the OFDM MIMO STBC system only required an Eb / No value of 10.5 dB to achieve BER 10-4. The eye pattern generated by the OFDM MIMO ZF system was more closed and the dispersion of constellation signals away from the ideal point while OFDM MIMO STBC system displayed a more open eye pattern and the dispersion of its constellation signal closer to the ideal point. It indicated more ISI occurs in the OFDM MIMO ZF system than that in OFDM MIMO STBC system.

Massive multi-user (MU) multiple-input multiple-output (MIMO) promises significant gains in spectral efficiency compared to traditional, small-scale MIMO technology. Linear equalization algorithms, such as zero forcing (ZF) or minimum mean-square error (MMSE)-based methods, typically rely on centralized processing at the base station (BS), which results in (i) excessively high interconnect and chip input/output data rates, and (ii) high computational complexity. In this paper, we investigate the achievable rates of decentralized equalization that mitigates both of these issues. We consider two distinct BS architectures that partition the antenna array into clusters, each associated with independent radio-frequency chains and signal processing hardware, and the results of each cluster are fused in a feed forward network. For both architectures, we consider ZF, MMSE, and a novel, non-linear equalization algorithm that builds upon approximate message passing (AMP), and we theoretically analyze the achievable rates of these methods. Our results demonstrate that decentralized equalization with our AMP-based methods incurs no or only a negligible loss in terms of achievable rates compared to that of centralized solutions.

Turbo codes are well known to be one of the error correction techniques which achieve closer results to the Shannon limit. Nevertheless, the specific performance of the code highly depends on the particular decoding algorithm used at the receiver. In this sense, the election of the decoding algorithm involves a trade off between the gain introduced by the code and the complexity of the decoding process. In this work we perform a thorough analysis of the different iterative decoding techniques and analyze their suitability for being implemented in the user terminals of new cellular and broadcast systems which are based on orthogonal frequency division multiplexing (OFDM). The analyzed iterative decoding algorithms are the max-log-MAP and the soft output Viterbi algorithm (SOVA), since both of them have a relative low computational complexity, simplifying their implementation in cost efficient terminals. Simulation results have been obtained for different encoder structures, block sizes and considering realistic channel conditions (an OFDM transmission over a wireless channel).

In this paper, we study the joint user pairing and resource allocation problem for uplink single carrier frequency-division multiple access (SC-FDMA) system with virtual multiple-input multiple-output (V-MIMO) implemented. Different from existing relevant researches, we consider a universal solution based on profit function for this problem instead of studying a particular scheduling policy, and then we explain that it is a MAX SNP-hard problem with high complexity. After that, we will propose a low-complexity heuristic algorithm called First User First (FuF), which is based on the idea of allocating resource to one user first. Moreover, in order to get a more accurate theoretical approximation to this problem, we will propose a constant factor approximation algorithm with polynomial-time complexity using local ratio technique. The simulation results of our algorithms show that the B-LRT algorithm has robust performance compared with other popular algorithms, while the FuF algorithm has lowest computation complexity at the expense of a little performance loss.

The power consumption is an essential issue for designers of mobile devices. Orthogonal Frequency Division Multiplexing (OFDM) suffers from its Peak – to – Average Power Ratio (PAPR) problem. The Discrete Fourier Transmission Spread OFDM (DFTS-OFDM) based on Single Carrier Frequency Division Multiple Access (SC-FDMA) has been widely adopted due to its lower peak-to-average power ratio (PAPR) of transmits signals compared with OFDM. There are three types of mapping in SCFDMA. These namely Localized FDMA (LFDMA), Distributed FDMA (DFDMA), and Interleaved FDMA (IFDMA). In this paper, we propose a modified SCFDMA. This is based on using Hadamard transform instead of Fast Fourier Transform (FFT). Utilizing LFDMA Mapping techniques this is proposed for uplink scenario of LTE. Simulation results show that the proposed scheme reduces PAPR compared to the conventional SCFDMA while the BER does not degraded.

Localization networks based on orthogonal frequency-division multiplexing (OFDM) ranging systems provide desirable location-awareness with commodity WiFi chipsets in harsh propagation conditions. Understanding the fundamental limits of OFDM ranging can guide the design and operation of these systems. Existing studies on these fundamental limits generally do not account for the processing impairments such as the estimation error of the phase offset and packet detection delay, yet ignoring processing impairments may lead to inaccurate evaluation of OFDM ranging accuracy. To address such inconsistency, we develop a framework to determine the fundamental limit of OFDM ranging, accounting for both channel parameters and processing impairments. In particular, we derive the equivalent Fisher information (EFI) for the propagation delay of the first path and quantify the effects of the number of multipaths, the number of channels, and processing impairments on the ranging accuracy through case studies. Numerical results verify the insights gained from the theoretical analysis.

This paper proposes a new physical layer architecture for uplink multiple access based on orthogonal frequency division multiplexing (OFDM). It achieves low peak-to-average power ratio (PAPR) and high reliability with low computational complexity at both the transmitter and receiver, targeting low-latency communications such as transmission of control information in machine-to-machine (M2M) and device-to-device (D2D) communications. Our approach is based on the judicious combination of subcarrier hopping and super-orthogonal convolutional codes (SOCC) for achieving high coding gain and frequency diversity, together with Golay complementary sequences for low PAPR signaling. By introducing non-orthogonal multiple access where the subcarriers of different users are partially overlapped, the overall bandwidth efficiency can be improved. Furthermore, the low PAPR nature improves the power efficiency and thus enhances the transmission range. Employing the successive interference cancellation at the receiver further mitigates the resulting multiple access interference.

The IEEE 802.16 standards are based on Orthogonal Frequency Division Multiplexing (OFDM) and multi-user OFDM (also known as OFDMA) for their desirable characteristics and potentials. Although well established, these standards only provide a framework of necessary mechanisms for deployable systems. Majority of the resource allocation issues are left unspecified. The conventional one-dimension scheduling cannot be readily applied in an 802.16 system. In this paper, a proportional fairness scheduling algorithm for 802.16 systems is proposed that utilizes the flexibility of frame division. Monte Carlo simulations are performed to evaluate these new methods in comparison to previously proposed techniques. The results indicate that the proposed methods lead to satisfactory performances, thanks to their improved two-dimensional feature.