Manar Mohaisen

Fixed-complexity vector perturbation with block diagonalization for MU-MIMO systems

Block diagonalization (BD) is an attractive technique that transforms the multi-user multiple-input multiple-output (MU-MIMO) channel into parallel single-user MIMO (SU-MIMO) channels with zero inter-user interference (IUI). In this paper, we combine the BD technique with two deterministic vector perturbation (VP) algorithms that reduce the transmit power in MU-MIMO systems with linear precoding. These techniques are the fixed-complexity sphere encoder (FSE) and the QR-decomposition with M-algorithm encoder (QRDM-E). In contrast to the conventional BD VP technique, which is based on the sphere encoder (SE), the proposed techniques have fixed complexity and a tradeoff between performance and complexity can be achieved by controlling the size of the set of candidates for the perturbation vector. Simulation results and analysis demonstrate the properness of the proposed techniques for the next generation mobile communications systems which are latency and computational complexity limited. In MU-MIMO system with 4 users each equipped with 2 receive antennas, simulation results show that the proposed BD-FSE and BD-QRDM-E outperforms the conventional BD-THP (Tomlinson Harashima precoding) by 5.5 and 7.4dB, respectively, at a target BER of 10−4.

Radio Transmission Performance of EPCglobal Gen-2 RFID System

In this paper, we analyze the performance of the encoding and the modulation processes in the downlink and uplink of the EPCglobal Gen2 system through the analysis and simulation. Furthermore, the synchronization issues on time and frequency domain and the preamble architecture are evaluated. Through the simulation in the uplink, we find that the detection probability of FM0 and Miller coding approaches 1 at 13 dB Eb/N0.

Detection Techniques for MIMO Multiplexing: A Comparative Review

Multiple-input multiple-output (MIMO) multiplexing is an attractive technology that increases the channel capacity without requiring additional spectral resources. The design of low complexity and high performance detection algorithms capable of accurately demultiplexing the transmitted signals is challenging. In this technical survey, we introduce the state-of-the-art MIMO detection techniques. These techniques are divided into three categories, viz. linear detection (LD), decision-feedback detection (DFD), and tree-search detection (TSD). Also, we introduce the lattice basis reduction techniques that obtain a more orthogonal channel matrix over which the detection is done. Detailed discussions on the advantages and drawbacks of each detection algorithm are also introduced. Furthermore, several recent author contributions related to MIMO detection are revisited throughout this survey.

Maximum-Likelihood Co-Channel Interference cancellation with power control for cellular OFDM networks

In cellular orthogonal frequency division multiplexing (OFDM) networks, co-channel interference (CCI) leads to severe degradation in the BER performance. To solve this problem, maximum-likelihood estimation (MLE) CCI cancellation scheme has been proposed in the literature. MLE CCI cancellation scheme generates weighted replicas of the transmitted signals and selects replica with the smallest Euclidean distance from the received signal. When the received power of the desired and interference signals are nearly the same, the BER performance is degraded. In this paper, we propose an improved MLE CCI canceler with closed-loop Power Control (PC) scheme capable of detecting and combating against the equal received power situation at the mobile station (MS) receiver by using the newly introduced parameter power ratio (PR). At cell edge where signal to interferer ratio (SIR) is considered to have average value between -5 and 10 dB, computer simulations show that the proposed closed-loop PC scheme has a gain of 7 dB at 28 km/h and about 2 dB at 120 km/h.

Parallel QR Decomposition in LTE-A systems

The QR Decomposition (QRD) of communication channel matrices is a fundamental prerequisite to several detection schemes in Multiple-Input Multiple-Output (MIMO) communication systems. Herein, the main feature of the QRD is to transform the non-causal system into a causal system, where consequently efficient detection algorithms based on the Successive Interference Cancellation (SIC) or Sphere Decoder (SD) become possible. Also, QRD can be used as a light but efficient antenna selection scheme. In this paper, we address the study of the QRD methods and compare their efficiency in terms of computational complexity and error rate performance. Moreover, a particular attention is paid to the parallelism of the QRD algorithms since it reduces the latency of the matrix factorization.

Fixed-complexity sphere encoder for multi-user MIMO systems

In this paper, we propose a fixed-complexity sphere encoder (FSE) for multi-user multi-input multi-output (MU-MIMO) systems. The proposed FSE accomplishes a scalable tradeoff between performance and complexity. Also, because it has a parallel tree-search structure, the proposed encoder can be easily pipelined, leading to a tremendous reduction in the preceding latency. The complexity of the proposed encoder is also analyzed, and we propose two techniques that reduce it. Simulation and analytical results demonstrate that in a 4 × 4 MU-MIMO system, the proposed FSE requires only 11.5% of the computational complexity needed by the conventional QR decomposition with M-algorithm encoder (QRDM-E). Also, the encoding throughput of the proposed encoder is 7.5 times that of the QRDM-E with tolerable degradation in the BER performance, while achieving the optimum diversity order.

On Improving the Efficiency of the Fixed-Complexity Sphere Decoder

Fixed-complexity sphere decoder (FSD), which con- sists of ordering stage and tree-search stage, achieves a quasi- ML performance while requiring a fixed computational ef- fort independent of the noise power and channel conditioning. Nevertheless, it requires a specific signal ordering using the VBLAST algorithm which has a high complexity due to the iterative pseudo-inversion of the channel matrix. In this paper, we propose two schemes to reduce the complexity of FSD algorithm in the ordering and tree-search stages, respectively, while achieving quasi-ML performance. In the ordering stage, we propose QR-decomposition-based FSD signal ordering (FSD- SQRD) that requires only a few number of additional complex flops compared to the unsorted QRD. In the tree-search stage, we introduce a threshold-based complexity reduction approach for FSD depending on the reliability of the signal with the lowest received SNR. Numerical results show that in a 4×4 system, the proposed FSD-SQRD requires only 17.2% of the computational efforts required by a reduced-complexity VBLAST approach. Moreover, using 16-QAM, simulation results show that when the proposed threshold-based approach is employed, FSD requires only 69.5% of its full complexity.

Adaptive Parallel and Iterative QRDM Algorithms for Spatial Multiplexing MIMO Systems

QR-decomposition with M-algorithm (QRDM) achieves quasi-ML performance in multiple-input multiple- output (MIMO) multiplexing systems. Nevertheless, QRDM per- forms avoidable computations because of its systematic search strategy and its unawareness of the channel and noise conditions. Another drawback is that QRDM has a sequential nature which limits the capabilities of pipelining. In this paper, we propose semi-ML adaptive parallel QRDM (APQRDM) and iterative QRDM (AIQRDM) algorithms based on set grouping. Using the set grouping, the tree-search stage of QRDM algorithm is divided into partial detection phases (PDP). Therefore, when the tree- search stage of QRDM is divided into 4 PDPs, the APQRDM latency is one fourth of that of the QRDM, and the hardware requirements of AIQRDM is approximately one fourth of that of QRDM. Moreover, simulation results show that in 4 × 4 system and at Eb/N0 of 14 dB, APQRDM decreases the average computational complexity to approximately 43% of that of the conventional QRDM. Also, at Eb/N0 of 0dB, AIQRDM reduces the computational complexity to about 54% and the average number of metric comparisons to approximately 10% of those required by the conventional QRDM and AQRDM.

An Algorithm for Iterative Detection and Decoding MIMO-OFDM HARQ with Antenna Scheduling

In this paper, a multiple-input-multiple-output (MIMO) hybrid-automatic repeat request (HARQ) algorithm with antenna scheduling is proposed. It retransmits the packet using scheduled transmit antennas according to the state of the communication link, instead of retransmitting the packet via the same antennas. As a result, a combination of conventional HARQ systems, viz. chase combining (CC) and incremental redundancy (IR) are used to achieve better performance and lower redundancy. The proposed MIMO-OFDM HARQ system with antenna scheduling is shown to be superior to conventional MIMO HARQ systems, due to its spatial diversity gain.

From Linear Equalization to Lattice-Reduction-Aided Sphere-Detector as an Answer to the MIMO Detection Problematic in Spatial Multiplexing Systems

Employing multiple antennas at both the transmitter and the receiver linearly boosts the channel capacity by min (nT , nR), where nT and nR are the number of transmit and receive antennas, respectively A. Telatar (1999). Multiple-Input Multiple-Output (MIMO) technologies are classified into three categories: (i) MIMO diversity, (ii) MIMO Spatial Multiplexing (MIMO-SM) and (iii) beamforming that will not be addressed here since it particularly deals with transmitter algorithms. MIMO diversity techniques are deployed to increase the reliability of communications by transmitting or receiving multiple copies of the same signal at different resource entities of the permissible dimensions, i.e., time, frequency, or space. In contrast, the target of MIMO-SM is to increase the capacity of the communication channel. To this end, independent symbols are transmitted simultaneously from the different transmit antennas. Due to its attracting implementation advantages, Vertical Bell Laboratories Layered Space-Time (V-BLAST) transmitter structure is often used in the practical communication systems P. Wolniansky, G. Foschini, G. Golden, and R. Valenzuela (1998). In 3GPP Long Term Evolution-Advanced (3GPP LTE-A) 3GPP (2009), the challenge of de-multiplexing the transmitted symbols via SM techniques, i.e. detection techniques, stands as one of the main limiting factors in linearly increasing system’s throughput without requiring additional spectral resources. The design of detection schemes with high performance, low latency, and applicable computational complexity is being a challenging research topic due to the power and latency limitations of the mobile communication systems M. Mohaisen, H.S. An, and K.H.Chang (2009).