In this work, Survey and investigation on inter symbol interference (ISI) and inter carrier interference (ICI) due to either carrier frequency offset or timing offset issues and interference mitigation schemes available, compare and analyze their bit error rate performance to various schemes for OFDM and MIMO-OFDM systems. Efforts have been made to develop an efficient interference cancelling receiver for ISI and ICI, algorithms to be implemented on MATLAB environment for OFDM and MIMO-OFDM which are not available in literature.
This book introduces the development of self-interference (SI)-cancellation techniques for full-duplex wireless communication systems. The authors rely on estimation theory and signal processing to develop SI-cancellation algorithms by generating an estimate of the received SI and subtracting it from the received signal. The authors also cover two new SI-cancellation methods using the new concept of active signal injection (ASI) for full-duplex MIMO-OFDM systems. The ASI approach adds an appropriate cancelling signal to each transmitted signal such that the combined signals from transmit antennas attenuate the SI at the receive antennas. The authors illustrate that the SI-pre-cancelling signal does not affect the data-bearing signal. This book is for researchers and professionals working in wireless communications and engineers willing to understand the challenges of deploying full-duplex and practical solutions to implement a full-duplex system. Advanced-level students in electrical engineering and computer science studying wireless communications will also find this book useful as a secondary textbook.
"Full-duplex operation for wireless communications can potentially double the spectral efficiency, compared to half-duplex operation, by using the same wireless resource to transmit and receive at the cost of a large power difference between the high-power self-interference (SI) from its own transmitted signal and the low-power intended signal received from the other distant transceiver. The SI can be gradually reduced by a combination of radiofrequency (RF) and baseband cancellation stages. Each stage requires the estimation of the different distortions that the SI endures such as the SI channel and the transceiver nonlinearities. This thesis deals with the development of SI-cancellation techniques that are well-adapted to the full-duplex operation.First, we recognize the sparseness of the SI channel and exploit it to develop a compressedsensing (CS) based SI channel estimator. The obtained estimate is used to reduce the SI at the RF prior to the receiver low-noise amplifier and analog-to- digital converter to avoid overloading them. To further reduce the SI, a subspace-based algorithm is developed to jointly estimate the residual SI channel, the intended channel between the two transceivers and the transmitter nonlinearities for the baseband cancellation stage. Including the unknown received intended signal in the estimation process represents the main advantage of the proposed algorithm compared to previous data-aided estimators that assume the intended signal as additive noise. By using the second-order statistics of the received signal, it is possible to obtain the noise subspace and then to estimate the different coefficients without knowing the intended signal. Depending on the number of transmit and receive antennas, we propose to use either the received signal or a combination of the received signal and its complex conjugate. Also, we develop a semi-blind maximum likelihood (ML) estimator that combines the known pilot and unknown data symbols from the intended transceiver to formulate the likelihood function. A closed-form expression of the ML solution is first derived, and an iterative procedure is developed to further improve the estimation performance at moderate to high signal-to-noise ratio. Simulations show significant improvement in SI-cancellation gain compared to the data-aided estimators. Moreover, we present two new SI-cancellation methods using active signal injection (ASI) for full-duplex MIMO-OFDM systems. The ASI approach adds an appropriate cancelling signal to each transmitted signal such that the combined signals from transmit antennas attenuate the SI at the receive antennas. In the first method, the SI-pre-cancelling signal uses some reserved subcarriers which do not carry data. In the second method, the constellation points are dynamically extended within the constellation boundary in order to minimize the received SI. Thus, the SI-pre-cancelling signal does not affect the data-bearing signal. Simulation results show that the proposed methods considerably reduce the SI at a modest computational complexity." --
Multicarrier (MC) Modulation attracts a lot of attention for high speed wireless transmissions because of its capability to cope with frequency selective fading channels turning the wideband transmission link into several narrowband subchannels whose equalization, in some situations, can be performed independently and in a simple manner. Nowadays, orthogonal frequency division multiplexing (OFDM) with the cyclic prefix (CP) insertion is the most widespread modulation among all MC modulations, and this thanks to its simplicity and its robustness against multipath fading using the cyclic prefix. Systems or standards such as ADSL or IEEE802.11a have already implemented the CP-OFDM modulation. Other standards like IEEE802.11n combine CP-OFDM and multiple-input multiple-output (MIMO) in order to increase the bit rate and to provide a better use of the channel spatial diversity. Nevertheless, CP-OFDM technique causes a loss of spectral efficiency due to the CP as it contains redundant information. Moreover, the rectangular prototype filter used in CP-OFDM has a poor frequency localization. This poor frequency localization makes it difficult for CP-OFDM systems to respect stringent specifications of spectrum masks.To overcome these drawbacks, filter-bank multicarrier (FBMC) was proposed as an alternative approach to CP-OFDM. Indeed, FBMC does not need any CP, and it furthermore offers the possibility to use different time-frequency well-localized prototype filters which allow much better control of the out-of-band emission. In the literature we find several FBMC systems based on different structures. In this thesis, we focus on the Saltzberg's scheme called OFDM/OQAM (or FBMC/OQAM). The orthogonality constraint for FBMC/OQAM is relaxed being limited only to the real field while for OFDM it has to be satisfied in the complex field. Consequently, one of the characteristics of FBMC/OQAM is that the demodulated transmitted symbols are accompanied by interference terms caused by the neighboring transmitted data in time-frequency domain. The presence of this interference is an issue for some MIMO schemes and until today their combination with FBMC remains an open problem.The aim of this thesis is to study the combination between FBMC and MIMO techniques, namely spatial multiplexing with ML detection. In the first part, we propose to analyze different intersymbol interference (ISI) cancellation techniques that we adapt to the FBMC/OQAM with MIMO context. We show that, in some cases, we can cope with the presence of the inherent FBMC interference and overcome the difficulties of performing ML detection in spatial multiplexing with FBMC/OQAM. After that, we propose a modification in the conventional FBMC/OQAM modulation by transmitting complex QAM symbols instead of OQAM ones. This proposal allows to reduce considerably the inherent interference but at the expense of the orthogonality condition. Indeed, in the proposed FBMC/QAM,the data symbol and the inherent interference term are both complex. Finally, we introduce a novel FBMC scheme and a transmission strategy in order to avoid the inherent interference terms. This proposed scheme (that we call FFT-FBMC) transforms the FBMC system into an equivalent system formulated as OFDM regardless of some residual interference. Thus, any OFDM transmission technique can be performed straightforwardly to the proposed FBMC scheme with a corresponding complexity growth. We develop the FFT-FBMC in the case of single-input single-output (SISO) configuration. Then, we extend its application to SM-MIMO configuration with ML detection and Alamouti coding scheme.
This work describes the OFDM-based MIMO Radar-Communication System, intended for operation in a multiple-user network, especially the automotive sector in the vehicle-to vehicle/infrastructure network. The OFDM signals however are weak towards frequency offsets causing subcarrier misalignment and corrupts the radar estimation and the demodulation of the communication signal. A simple yet effective interference cancellation algorithm is detailed here with real time measurement verification.
Multiple-input multiple-output (MIMO) is a promising wireless communication technique to boost the wireless link capacity without requiring additional power or bandwidth. Combined with orthogonal frequency division multiplexing (OFDM) the MIMO OFDM system is considered an attractive candidate for high data rate wideband wireless communications over frequency selective channels. 4G-LTE, WiFi (802.11) and WiMax (802.16e) all adopt MIMO OFDM in their standards. ☐ In real world applications of MIMO OFDM system, diversified sources of interference often exist and significantly influence the system performance of MIMO OFDM. Firstly let's consider the single user point-to-point MIMO OFDM system. The interference may be often caused by a long time delay spread of the channel. Typically MIMO OFDM systems resort to cyclic prefix (CP) to protect the system from interference. The simple one-tap equalization in OFDM also relies on the assumption that the CP length is at least as large as the channel memory length. However, in a number of applications, the sufficient CP length requirement is not practically satisfied for various reasons. For example, in the next generation of WiFi standard, outdoor transmission is much more involved. The time delay spread of the outdoor channel may be much longer than that considered in the typical channel models in the current WiFi standards. If the current OFDM symbol structure is inherited, we may face the insufficient CP problem in the outdoor transmission scenario. Next consider the interference scenario in MIMO OFDM cooperative communication system. In the emerging 5G cooperative communication system, the relay node may adopt the amplify-and-forward (AF) relay protocol and the in-band full-duplex (FD) mode. The simultaneous transmission and reception at the relay node gives rise to severe self loopback interference. All the mentioned types of interference have detrimental influence on the error rate performance of the MIMO OFDM system. Therefore signal designs for MIMO OFDM system must take interference cancellation or management into consideration. ☐ In the first topic, a new interference nulling based channel independent precoding for MIMO OFDM systems of nt transmit and nr receive antennas with insufficient CP is proposed. When the CP length is insufficient, intercarrier interference (ICI) from the symbols in the current transmission block and interblock interference (IBI) from the previous transmission block occur in the OFDM system. To cope with ICI and IBI induced by the insufficient CP, we have proposed a design framework to completely nulling the IBI. In our first channel independent precoding scheme, no channel state information is needed. When MIMO OFDM system equips the same number of transmit and receive antennas or the transmit antennas are more than the receive antennas, we have shown that precoding at the transmitter combined with interference nulling at the receiver can assist to either cancel interblock interference (IBI) or separate the subspace occupied by IBI from the subspace used for information symbols. When the transmit antennas are less than the receive antennas, it is demonstrated that information symbols can be decoded without any precoding at the transmitter but just with interference nulling and block linear equalization at the receiver. ☐ In the next topic, we consider a robust precoder design which combines statistical CSI at the transmitter and the interference nulling based precoding structure to gain a better performance compared to the channel independent precoding scheme. Statistical channel state information at the transmitter in the form of covariance matrix of the MIMO OFDM channel matrix is utilized to perform the robust precoding. Standard optimization problem is formulated with regard to the largest mean square error (MSE) of the minimum mean square error (MMSE) equalized symbol in the insufficient CP signal model. By employing convex optimization technique, a closed-form solution is derived for the optimization problem. Since the average MSEs are set equal using this precoder, the BER performance is better than our previously proposed channel independent precoder. ☐ In the third topic, we consider the OFDM-based transmission in the AF full duplex relay system with residual self-interference. A delay diversity OFDM (DD OFDM) transmission scheme in amplify-and-forward (AF) full-duplex relay systems is investigated. One direct source-to-destination link, one relay forwarding link and residual self-interference (RSI) are considered in the system. The necessary cyclic prefix (CP) length is investigated and a suitable AF relay protocol in the full-duplex relay OFDM system is proposed. This paper demonstrates that the AF relay link and the direct source-to-destination link can be combined to provide spatial diversity. The key is that the DD OFDM scheme is used to transform the spatial diversity into increased channel frequency diversity that is further exploited by using the bit-interleaved coding. The BER performance of the proposed system is verified by simulation results.
Multiple-input multiple-output (MIMO) antennas can be exploited to provide high data rate using a limited bandwidth through multiplexing gain. MIMO combined with orthogonal frequency division multiplexing (OFDM) could potentially provide high data rate and high spectral efficiency in frequency-selective fading channels. MIMO-OFDM technology has been widely employed in modern communication systems, such as Wireless Local Area Network (WLAN), Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX). However, most of the conventional schemes either are computationally prohibitive or underutilize the full performance gain provided by the inherent merits of MIMO and OFDM techniques. In the first part of this dissertation, we firstly study the channel matrix inversion which is commonly required in various MIMO detection schemes. An algorithm that exploits second-order extrapolation in the time domain is proposed to efficiently reduce the computational complexity. This algorithm can be applied to both linear detection and non-linear detection such as ordered successive interference cancellation (OSIC) while maintaining the system performance. Secondly, we study the complexity reduction for Lattice Reduction Aided Detection (LRAD) of MIMO-OFDM systems. We propose an algorithm that exploits the inherent feature of unimodular transformation matrix that remains the same for relatively highly correlated frequency components. This algorithm effectively eliminates the redundant brute-force lattice reduction iterations among adjacent subcarriers. Thirdly, we analyze the impact of channel coherence bandwidth on two LRAD algorithms. Analytical and simulation results demonstrate that carefully setting the initial calculation interval according to the coherence bandwidth is essential for both algorithms. The second part of this dissertation focuses on efficient multi-user (MU) scheduling and coordination for the uplink of WLAN that uses MIMO-OFDM techniques. On one hand, conventional MU-MIMO medium access control (MAC) protocols require large overhead, which lowers the performance gain of concurrent transmissions rendered by the multi-packet reception (MPR) capability of MIMO systems. Therefore, an efficient MU-MIMO uplink MAC scheduling scheme is proposed for future WLAN. On the other hand, single-user (SU) MIMO achieves multiplexing gain in the physical (PHY) layer and MU-MIMO achieves multiplexing gain in the MAC layer. In addition, the average throughput of the system varies depending on the number of antennas and users, average payload sizes, and signal-to-noise-ratios (SNRs). A comparison on the performance between SU-MIMO and MU-MIMO schemes for WLAN uplink is hence conducted. Simulation results indicate that a dynamic switch between the SU-MIMO and MU-MIMO is of significance for higher network throughput of WLAN uplink.
The common thread of the research in this dissertation is to introduce novel interference resilient techniques in multiuser wireless communication systems where the goal of these techniques is to improve system throughput or efficiency and guarantee reliable communication. More specifically, in the first part, we consider the problem of multiplexing wireless data transmission in two-way communication (TWC) channels. Using traditional wireless packet switching methods bidirectional communication tends to double the interference (or time) needed to complete the session. We propose new interference resilient schemes by combining the so called ``two-way relaying'' scheme with a distributed randomized space-time block coding (RSTBC) strategy. RSTBC is a decentralized cooperative technique that ensures diversity gains through the recruitment of multiple uncoordinated relays, with virtually no signaling overhead to enlist relays. In this problem, RSTBC is applied to two-way relaying wireless networks which, when two terminals want to send a message to each other, can potentially improve the network throughput by allowing them to exchange data over two or three time slots via bidirectional relay communications. Specifically, two decode-and-forward (DF) relaying strategies are considered which take up only two time slots. In the first slot the two sources transmit simultaneously. In the former scheme which we refer to as decode and forward both (DFB) RSTBC, only relays which can reliably decode both source blocks via joint maximum likelihood (ML) decoding cooperate, and do so by modulating the bit-level XOR of the decoded data through a single RSTBC. In the latter scheme called decode and forward any (DFA) RSTBC, the relays cooperate in the second slot also when they can decode only one of the two source data. In this case each source data that is decoded is mapped into an independent RSTBC. If the relay decoded reliably both sources, after cancellation of the strong interference, then it sends the two RSTBCs encoding the symbol vectors from each of the sources. A randomized forwarding scheme is also proposed for three-time-slot relaying, which is also a DFA strategy, although without joint decoding or interference cancellation after the first slot. In addition to more judicious transmission and relaying policies, a key ingredient of future wireless network will be enhanced spectrum sensing. This is motivated by the wide adoption of Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems, which offer significant degrees of freedom in encoding data, but at the same time result in a complex spatio-temporal landscape of interference. We combine recent advances in array processing and compressed channel sensing, to solve the problem of estimating the covariance of an asynchronous network of MIMO-OFDM sources. We specifically focus on spectrum sensing (SS) in cognitive radio (CR) systems, since it is of paramount importance to approach the capacity limits for the Secondary Users (SU), while ensuring the undisturbed transmission of Primary Users (PU). In this problem, we formulate a cognitive radio systems spectrum sensing problem in which SU, with multiple receive antennas, senses a channel shared among multiple asynchronous PUs transmitting MIMO-OFDM signals. Lastly, we study online learning and stochastic optimization in cognitive radio system at MAC layer. The typical Compressive Sensing problem models an observer that wants to recover a sparse N dimensional vector from K linear projections of the vector. We combine the ideas of opportunistic spectrum sensing with compressive sensing and introduce the Cognitive Compressive Sensing (CCS) problem which models a cognitive receiver that uses Bayesian beliefs on a dynamically changing sparse vector representing measurements from the signals occupying the sub-channels. The CR objective is to optimally choose the K linear projections with the objective of maximizing a reward from the inference of the sparse vector support. We formulate CCS as a Restless Multi-Armed Bandit problem, generalizing the popular Cognitive Spectrum Sensing model, in which the CR can sense K out of the N sub-channels. We derive the myopic sensing policy that leverages on the beliefs to its inferences. We also propose a greedy counterpart of the myopic sensing policy algorithm with considerably less required computations. While in general the optimum policy remains elusive, we provide sufficient conditions in which in the limit for large K and N the greedy policy is optimum.
This book is written for graduate students and professionals concerned with MIMO systems. It reviews mostknown multiple antenna techniques for single-use point-to-point systems, from how multiple antennas help provide diversity and multiplexing to the detection techniques for these systems. This book covers the main fields of MIMO systems with 10 chapters; each chapter covers either base-bandsignal processing aspect or application.
