Waleed Al-Hanafy

Joint Low-Complexity Equalization and Carrier Frequency Offsets Compensation Scheme for MIMO SC-FDMA Systems

Due to their noise amplification, conventional Zero-Forcing (ZF) equalizers are not suited for interference-limited environments such as the Single-Carrier Frequency Division Multiple Access (SC-FDMA) in the presence of Carrier-Frequency Offsets (CFOs) . Moreover, they suffer increasing complexity with the number of subcarriers and in particular with Multiple-Input Multiple-Output (MIMO) systems. In this letter, we propose a Joint Low-Complexity Regularized ZF (JLRZF) equalizer for MIMO SC-FDMA systems to cope with these problems. The main objective of this equalizer is to avoid the direct matrix inversion by performing it in two steps to reduce the complexity. We add a regularization term in the second step to avoid the noise amplification. From the obtained simulation results, the proposed scheme is able to enhance the system performance with lower complexity and sufficient robustness to estimation errors.

Chaotic Interleaving for Robust Image Transmission with LDPC Coded OFDM

This paper presents a new technique for progressive image transmission over low-density parity-check coded orthogonal frequency division multiplexing (LDPC-OFDM) system. This technique adopts chaotic Baker map to improve the performance and reduce the peak-to-average power ratio (PAPR) of the OFDM signal. It helps improving the error resilient ability and also enhancing the efficiency of progressive image transmission over frequency selective fading channels. The proposed technique can effectively resist the fading impact of the frequency selective channels using simple frequency domain equalization. The proposed technique also utilizes the set partitioning in hierarchical trees as a source coding algorithm for the transmitted images. The distinctive feature of the proposed technique is that the transmitted data sequence has less data correlation, which leads to minimizing the PAPR. Simulation results show that the proposed technique improves the visual quality of the received images and reduces the PAPR of the OFDM signal as well.

C32. Greedy power allocation algorithm for proportional resource allocation in multi-user OFDM systems

Multi-User Orthogonal Frequency Division Multiplexing (MU-OFDM) is an efficient technique for achieving high downlink capacity in high-speed communication systems. A key issue in MU-OFDM is the allocation of the OFDM subcarriers and power to users sharing the channel. In this paper, a proportional rate-adaptive resource allocation algorithm for MU-OFDM is presented. Subcarrier and power allocation are carried out sequentially to reduce the complexity. The low complexity proportional subcarriers allocation is followed by Greedy Power Allocation (GPA) to solve the rate-adaptive resource allocation problem with proportional rate constraints for MU-OFDM systems. It improves on the work of Wong et al. in this area by introducing optimal GPA that achieves approximate rate proportionality, while maximizing the total sum-rate capacity of MU-OFDM. It is shown through simulation that the proposed GPA algorithm performs better than the algorithm of Wong et al. by achieving higher total capacities with the same computational complexity, especially, at higher number of users.

Broadband SVD and non-linear precoding applied to broadband MIMO channels

We address the problem of precoding and equalisation of broadband MIMO systems. A new non-block based methods is based on a broadband singular value decomposition, which can decouple a broadband MIMO channel into independent dispersive SISO subchannels. We thereafter apply Tomlinson-Harashima precoding to mitigate the dispersiveness of these SISO subchannels. We present arguments why this is a suitable approach compared to existing methods, underlined by some simulation results.

Adaptive Resource Allocation Algorithms for Multi-user MIMO-OFDM Systems

Radio resource allocation to the system users is the key challenge issue in multi-user orthogonal frequency division multiplexing (MU-OFDM) systems. In this paper, an efficient and low-complexity proportional rate-adaptive radio resource (sub-carrier and power) allocation algorithm for MU-OFDM is proposed to maximize the sum-rate capacity of the system and achieve acceptable users’ rates fairness. Three-dimensional (spatial, frequency, and multi-user) greedy power allocation (GPA) algorithms for the MU multi-input multi-output OFDM (MU MIMO-OFDM) systems are proposed. The proposed algorithms start with spatial sub-carrier allocation followed by an optimal two-dimensional spatial-frequency GPA (SFGPA) step, which exploits both the spatial and frequency diversities. Therefore, spatial, frequency, and multi-user diversities are exploited by the proposed three-dimensional GPA algorithms. Several experiments are carried out to test the performance of the proposed three-dimensional GPA algorithms in terms of sum-rate capacity. The optimal solution is achieved by the three-dimensional dynamic sub-carrier-SFGPA with average gain (DS-SFGPA-AG) algorithm, which achieves the best sum-rate capacity performance compared with the other power allocation algorithms. The performance of the DS-SFGPA-AG algorithm is also analyzed and compared for the four OFDM-based systems; single-user (SU) OFDM, SU MIMO-OFDM, MU OFDM, and MU MIMO-OFDM. The MU MIMO-OFDM system with adaptive sub-carrier and power allocation outperforms the other systems.

Comparison of precoding methods for broadband MIMO systems

In this paper we investigate non-linear precoding solutions for the problem of broadband multiple-input multiple-output (MIMO) systems. Based on a broadband singular value decomposition (BSVD) we can decouple a broadband MIMO channel into independent dispersive spectrally majorised single-input single-output (SISO) subchannels. Bit loading is proposed to optimally utilise these SISO subchannels after mitigating their individual inter-symbol-interference (ISI) using Tomlinson-Harashima precoding (THP). This method is benchmarked against recent results of both MMSE linear and THP designed for frequency-selective MIMO channels. Simulation results show that better bit-error-ratio (BER) can be achieved especially for higher throughput targets when compared to the benchmark.

Efficient Image Communication in PAPR Distortion Cases

AbstractIn this paper, a proposed method for Peak-to-Average Power Ratio (PAPR) reduction of Orthogonal Frequency Division Multiplexing (OFDM) signals based on discrete transforms is presented for robust image communication. One of the discrete transforms such as discrete wavelet transform, discrete cosine transform, or discrete sine transform is applied to modify the OFDM signal at the output of the inverse fast Fourier transform stage. We first present the proposed OFDM system model with trigonometric transforms for PAPR reduction. Trigonometric transforms improve the performance of the OFDM system, and reduce the PAPR of the OFDM signal. Then, this scheme has been utilized for progressive image transmission using low-density parity-check coded OFDM over frequency-selective fading channels. The set partitioning in hierarchical trees algorithm is used for source coding of the images to be transmitted. The proposed scheme effectively resists the fading impact of frequency-selective fading channels using simple frequency-domain equalization. Simulation experiments are performed for a variety of multipath fading channels. We also propose a chaotic interleaving scheme based on the 2-D chaotic Baker map for PAPR reduction of OFDM signals. The distinctive feature of this scheme is that the transmitted signal has less correlation between samples, and hence the PAPR is minimized.

An improved adaptive transmission scheme for high speed communication systems

In this paper, an improved transmission scheme for high speed communication systems is introduced. This scheme combines a low complexity discrete bit loading algorithm with a simplified Maximum Ratio Combining (MRC) pre-equalization scheme at the transmitter for maximizing the data throughput of Orthogonal Frequency Division Multiplexing (OFDM) systems. Results of computer simulations show that pre-equalization is a very effective scheme for improving the performance of the proposed bit loading algorithm, especially, in high speed communication systems.

Adaptive Per-spatial Stream Power Allocation Algorithms for Single-User MIMO-OFDM Systems

This paper presents adaptive per-spatial stream power allocation algorithms for Single User Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (SU MIMO-OFDM) systems. Three efficient and low-complexity Greedy Power Allocation (GPA) algorithms are proposed to maximize the throughput and spectral efficiency of the SU MIMO-OFDM systems. Firstly, the low-complexity pre-coded GPA algorithms are developed for the MIMO systems. The spatial sub-channels are created by applying the so-called Singular Value Decomposition (SVD) technique on the MIMO channel matrix, and then the Pre-GPA algorithms are applied to exploit the multi-path and spatial diversities. Secondly, the spatial and frequency diversities are exploited by adaptively allocating the system sub-carriers to the spatial sub-channels followed by Per-Spatial GPA (PSGPA). Finally, spatial multiplexing-based GPA algorithms are proposed to optimize the spectral efficiency of the SU MIMO-OFDM system. An optimal two-dimensional Spatial-Frequency GPA (SFGPA) algorithm is proposed to efficiently improve the average system spectral efficiency. The high computational complexity of the optimal SFGPA solution is simplified by proposing a low-complexity Per-Spatial GPA with Excess Power Moving down (PSGPA-EPMd) algorithm, which moves the per-spatial excess power downwards to enhance the spectral efficiency of the spatial multiplexing-based SU MIMO-OFDM systems. The proposed algorithms achieve better spectral efficiency and maximize the throughput in comparison with conventional algorithms.

Suboptimal Greedy Power Allocation Schemes for Discrete Bit Loading

We consider low cost discrete bit loading based on greedy power allocation (GPA) under the constraints of total transmit power budget, target BER, and maximum permissible QAM modulation order. Compared to the standard GPA, which is optimal in terms of maximising the data throughput, three suboptimal schemes are proposed, which perform GPA on subsets of subchannels only. These subsets are created by considering the minimum SNR boundaries of QAM levels for a given target BER. We demonstrate how these schemes can significantly reduce the computational complexity required for power allocation, particularly in the case of a large number of subchannels. Two of the proposed algorithms can achieve near optimal performance including a transfer of residual power between subsets at the expense of a very small extra cost. By simulations, we show that the two near optimal schemes, while greatly reducing complexity, perform best in two separate and distinct SNR regions.