767 research outputs found

    Full Diversity Space-Time Block Codes with Low-Complexity Partial Interference Cancellation Group Decoding

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    Partial interference cancellation (PIC) group decoding proposed by Guo and Xia is an attractive low-complexity alternative to the optimal processing for multiple-input multiple-output (MIMO) wireless communications. It can well deal with the tradeoff among rate, diversity and complexity of space-time block codes (STBC). In this paper, a systematic design of full-diversity STBC with low-complexity PIC group decoding is proposed. The proposed code design is featured as a group-orthogonal STBC by replacing every element of an Alamouti code matrix with an elementary matrix composed of multiple diagonal layers of coded symbols. With the PIC group decoding and a particular grouping scheme, the proposed STBC can achieve full diversity, a rate of (2M)/(M+2)(2M)/(M+2) and a low-complexity decoding for MM transmit antennas. Simulation results show that the proposed codes can achieve the full diversity with PIC group decoding while requiring half decoding complexity of the existing codes.Comment: 10 pages, 3 figures

    Multiuser MIMO-OFDM for Next-Generation Wireless Systems

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    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

    Physical-Layer Cooperation in Coded OFDM Relaying Systems

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    Mobile communication systems nowadays require ever-increasing data rate and coverage of wide areas. One promising approach to achieve this goal is the application of cooperative communications enabled by introducing intermediate nodes known as relays to support the transmission between terminals. By processing and forwarding the receive message at the relays, the path-loss effect between the source and the destination is mitigated. One major limit factor for relay assisted communications is that a relay cannot transmit and receive using the same physical resources. Therefore, a half-duplex constraint is commonly assumed resulting in halved spectral efficiency. To combat this drawback, two-way relaying is introduced, where two sources exchange information with each. On the other hand, due to the physical limitation of the relays, e.g., wireless sensor nodes, it's not possible to implement multiple antennas at one relay, which prohibits the application of multiple-input multiple-output (MIMO) techniques. However, when treating multiple relays as a cluster, a virtual antenna array is formed to perform MIMO techniques in a distributed manner. %This thesis aims at designing efficient one-way and two-way relaying schemes. Specifically, existing schemes from the literature are improved and new schemes are developed with the emphasis on coded orthogonal frequency division multiplexing (OFDM) transmissions. Of special interest is the application of physical-layer network coding (PLNC) for two-phase two-way relaying. In this case, a network coded message is estimated from the superimposed receive signal at the relay using PLNC schemes. The schemes are investigated based on a mutual information analysis and their performance are improved by a newly proposed phase control strategy. Furthermore, performance degradation due to system asynchrony is mitigated depending on different PLNC schemes. When multiple relays are available, novel cooperation schemes allowing information exchange within the relay cluster are proposed that facilitate distributed MIMO reception and transmission. Additionally, smart signaling approaches are presented to enable the cooperation at different levels with the cooperation overhead taken into account adequately in system performance evaluation

    Iterative Receiver for MIMO-OFDM System with ICI Cancellation and Channel Estimation

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    As a multi-carrier modulation scheme, Orthogonal Frequency Division Multiplexing (OFDM) technique can achieve high data rate in frequency-selective fading channels by splitting a broadband signal into a number of narrowband signals over a number of subcarriers, where each subcarrier is more robust to multipath. The wireless communication system with multiple antennas at both the transmitter and receiver, known as multiple-input multiple-output (MIMO) system, achieves high capacity by transmitting independent information over different antennas simultaneously. The combination of OFDM with multiple antennas has been considered as one of most promising techniques for future wireless communication systems. The challenge in the detection of a space-time signal is to design a low-complexity detector, which can efficiently remove interference resulted from channel variations and approach the interference-free bound. The application of iterative parallel interference canceller (PIC) with joint detection and decoding has been a promising approach. However, the decision statistics of a linear PIC is biased toward the decision boundary after the first cancellation stage. In this thesis, we employ an iterative receiver with a decoder metric, which considerably reduces the bias effect in the second iteration, which is critical for the performance of the iterative algorithm. Channel state information is required in a MIMO-OFDM system signal detection at the receiver. Its accuracy directly affects the overall performance of MIMO-OFDM systems. In order to estimate the channel in high-delay-spread environments, pilot symbols should be inserted among subcarriers before transmission. To estimate the channel over all the subcarriers, various types of interpolators can be used. In this thesis, a linear interpolator and a trigonometric interpolator are compared. Then we propose a new interpolator called the multi-tap method, which has a much better system performance. In MIMO-OFDM systems, the time-varying fading channels can destroy the orthogonality of subcarriers. This causes serious intercarrier interference (ICI), thus leading to significant system performance degradation, which becomes more severe as the normalized Doppler frequency increases. In this thesis, we propose a low-complexity iterative receiver with joint frequency- domain ICI cancellation and pilot-assisted channel estimation to minimize the effect of time-varying fading channels. At the first stage of receiver, the interference between adjacent subcarriers is subtracted from received OFDM symbols. The parallel interference cancellation detection with decision statistics combining (DSC) is then performed to suppress the interference from other antennas. By restricting the interference to a limited number of neighboring subcarriers, the computational complexity of the proposed receiver can be significantly reduced. In order to construct the time variant channel matrix in the frequency domain, channel estimation is required. However, an accurate estimation requiring complete knowledge of channel time variations for each block, cannot be obtained. For time- varying frequency-selective fading channels, the placement of pilot tones also has a significant impact on the quality of the channel estimates. Under the assumption that channel variations can be approximated by a linear model, we can derive channel state information (CSI) in the frequency domain and estimate time-domain channel parameters. In this thesis, an iterative low-complexity channel estimation method is proposed to improve the system performance. Pilot symbols are inserted in the transmitted OFDM symbols to mitigate the effect of ICI and the channel estimates are used to update the results of both the frequency domain equalizer and the PICDSC detector in each iteration. The complexity of this algorithm can be reduced because the matrices are precalculated and stored in the receiver when the placement of pilots symbols is fixed in OFDM symbols before transmission. Finally, simulation results show that the proposed MIMO-OFDM iterative receiver can effectively mitigate the effect of ICI and approach the ICI-free performance over time-varying frequency-selective fading channels

    A study of performance and complexity for IEEE 802.11n MIMO-OFDM GIS solutions

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