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Many different encoding algorithms for systematic polar codes (SPC) have been introduced since SPC was proposed in 2011. However, the number of the computing units of exclusive OR (XOR) has not been optimized yet. According to an iterative property of the generator matrix and particular lower triangular structure of the matrix, we propose an optimized encoding algorithm (OEA) of SPC that can reduce the number of XOR computing units compared with existing non-recursive algorithms. We also prove that this property of the generator matrix could extend to different code lengths and rates of the polar codes. Through the matrix segmentation and transformation, we obtain a submatrix with all zero elements to save computation resources. The proportion of zero elements in the matrix can reach up to 58.5% from the OEA for SPC when the code length and code rate are 2048 and 0.5, respectively. Furthermore, the proposed OEA is beneficial to hardware implementation compared with the existing recursive algorithms in which signals are transmitted bidirectionally.

This paper introduces two effective techniques to reduce the decoding complexity of turbo product codes (TPC) that use extended Hamming codes as component codes. We first propose an advanced hard-input soft-output (HISO) decoding algorithm, which is applicable if an estimated syndrome stands for double-error. In conventional soft-input soft-output (SISO) decoding algorithms, 2p (p: the number of least reliable bits) number of hard decision decoding (HDD) operations are performed to correct errors. However, only a single HDD is required in the proposed algorithm. Therefore, it is able to lower the decoding complexity. In addition, we propose an early termination technique for undecodable blocks. The proposed early termination is based on the difference in the ratios of double-error syndrome detection between two consecutive half-iterations. Through this early termination, the average iteration number is effectively lowered, which also leads to reducing the overall decoding complexity. Simulation results show that the computational complexity of TPC decoding is significantly reduced via the proposed techniques, and the error correction performance remains nearly the same in comparison with that of conventional methods.

In this paper, we study resource allocation in buffer-aided relay-assisted OFDMA networks. We consider utility-based stochastic optimization framework where there are constraints to be met either instantaneously or in average sense. Using the well-known Lyapunov drift-plus-penalty policy, we extract the instantaneous problem that needs to be solved in each slot to control the data admission and allocate the time slots, power, and subchannels. We propose the parameters that should be taken into account in utilizing the drift-plus-penalty policy in relay-assisted cellular networks, for providing fair data admission and satisfying the average power constraints. We introduce a low-complexity strategy for power and subchannel allocation and propose distributed and centralized algorithms to utilize it. Specifically, the proposed efficient dynamic distributed resource allocation (EDDRA) scheme is suitable for use in practice as it imposes less overhead on the system and splits the resource allocation tasks among the base station (BS) and the relays. Extensive simulation results show the effectiveness of the proposed parameters in meeting the objective and the constraints of the studied problem. We also show that the proposed EDDRA scheme has close performance to the proposed centralized one and outperforms an existing centralized scheme. 2015, Hajipour et al. Scopus

In this paper, we describe a simplified soft-output demapper designed to support coded multiple-input multiple-output orthogonal frequency-division multiplexing-based system utilizing only 3-bit soft information. The IEEE 802.11n standard requires relatively high punctured convolutional code rate of R=5/6 for spectrally efficient high-throughput data rate settings. In order to extract soft-bit information effectively without degrading the packet error rate performance, we introduce bit-rounding and effective-bit threshold adjustment techniques to achieve such.

Recently, a lattice reduction-aided (LRA) multiple-input multiple-output detection scheme has been proposed in junction with linear (as well as nonlinear) detectors. It is well known that these schemes provide a full diversity, and its complexity is comparable to that of linear detectors for the block fading channels. For the fast varying channels, however, the decoding complexity of LRA detection scheme is unreasonably high. This article proposes an efficient iterative lattice reduction (LR) scheme for an uplink system with two receive antennas at the base station and two users, each employing the Alamouti space-time block code (STBC). By taking advantage of the certain inherent STBC structure of transmitted symbols from users, the proposed scheme provides the same performance as a conventional LR while saving about 80% computational complexity. We also show that it can be successfully extended to handle the scenario where another interfering user, who is also employing the Alamouti STBC, is present.

Multiple-input multiple-output (MIMO) systems have an advantage of spectral efficiency compared to single-input single-output systems, which means that the MIMO systems have significantly higher data throughput. The V-BLAST (Vertical Bell Laboratories Layered Space Time) scheme is a popular transceiver structure which has relatively good performance. In the V-BLAST scheme, ordered successive interference cancellation (OSIC) technique was proposed as a possible efficient detection method in terms of performance and complexity. However, MIMO systems suffer from high complexity and implementation cost. As a practical solution, a technique called antenna selection has been introduced. Since the existing literature considered only the capacity-based selection, we develop an optimal selection method for V-BLAST scheme using OSIC detection with respect to error rate performance in this article. Its complexity is shown to be proportional to the fourth power of the number of transmit antennas. To reduce the complexity without significant performance degradation compared to the optimal selection method, a near-optimal selection method is also proposed. Simulation results show that the proposed selection method is very close to the performance of optimal selection.

This paper considers base station cooperation as an interference management technique for the downlink of a WiMAX network (IEEE 802.16 standard) with frequency reuse factor of 1. A low-complexity cooperative transmission and scheduling scheme is proposed that requires limited feedback from the users and limited information exchange between the base stations. The proposed scheme requires minor modifications to the legacy IEEE 802.16e systems. The performance of the proposed scheme is compared with noncooperative schemes with similar complexity through computer simulations. Results demonstrate that base station cooperation provides an attractive solution for mitigating the cochannel interference and increases the system spectral efficiency compared to traditional cellular architectures based on frequency reuse.

Receivers for long-code systems are for computational reasons usually based on simple matched-filter techniques, and hence suffer from multiaccess interference. Decorrelating RAKE and MMSE receivers do not have this problem but have not been widely studied due to the apparent complexity of the inversion of a large code matrix. Tong, van der Veen Dewilde, and Sung (IEEE Tr. Signal Proc., 2003) derived a blind decorrelating RAKE receiver (DRR) and channel estimation algorithm for long-code CDMA systems, and showed how it can be efficiently implemented. In this paper, we continue on that work. We propose both single-user and multiuser blind source-channel estimation algorithms by making use of an iterative estimation scheme initialized by the DRR. Simulation results show significant improvement, even in heavily loaded systems. Moreover, with an implementation based on time-varying system theory, the proposed algorithm can be implemented efficiently at a cost similar to the RAKE.

Tail-biting trellises are defined on a circular time axis and can have a smaller number of states than equivalent conventional trellises. Existing circular Viterbi algorithms (CVAs) on the tail-biting trellis are non-convergent and sub-optimal. In this study, we show that the net path metric of each tail-biting path is lower-bounded during the decoding process of the CVA. This property can be applied to remove unnecessary iterations of the CVA and results in a convergent maximum likelihood (ML) decoder. Simulation results show that the proposed algorithm exhibits higher decoding efficiency compared with other existing ML decoders.

International audience; Timing synchronization is a major issue for any communication system since it is essential to ensure its stable operation and reliable performance. In this paper, we compare two low-complexity synchronization algorithms for impulse radio ultra-wideband (IR-UWB) system, employing orthogonal pulse shape modulation (PSM). The two widely adopted modulation schemes for IR-UWB systems are binary pulse amplitude modulation and binary pulse position modulation. However, the possibility of generating orthogonal UWB pulses in recent years has motivated the use of orthogonal PSM which is particularly attractive as high-order modulation and also due to its possible robustness against ISI, and therefore is the focus of this paper. Relying on the unique signal format, the first algorithm applies simple overlap-add operation followed by energy detection to achieve synchronization. This approach is semi non-data-aided (NDA) because a part of the signal is specifically reserved to help enable synchronization. The other algorithm, on the other hand, exploits the discriminating nature of well-designed polarity codes and employs a series of code word matching and averaging operations to achieve synchronization. This approach is full NDA as there is no need to interrupt the data transmission. Based on the judicious change in the phase of transmitted signal applied for synchronization purposes, the second algorithm can also be used to extract synchronized aggregate templates. These templates are then used in demodulation, resulting in a low-complexity non-coherent alternative to complex Rake receivers. The two compared timing algorithms rely on simple overlap-add operations and thus remain operational under practical UWB settings. Simulation results are provided to demonstrate the efficient performance of proposed timing estimators.

Future wireless communication systems are demanding a more flexible physical layer. GFDM is a block filtered multicarrier modulation scheme proposed to add multiple degrees of freedom and to cover other waveforms in a single framework. In this paper, GFDM modulation and demodulation is presented as a frequency-domain circular convolution, allowing for a reduction of the implementation complexity when MF, ZF and MMSE filters are employed as linear demodulators. The frequency-domain circular convolution shows that the DFT used in the GFDM signal generation can be seen as a precoding operation. This new point-of-view opens the possibility to use other unitary transforms, further increasing the GFDM flexibility and covering a wider set of applications. The following three precoding transforms are considered in this paper to illustrate the benefits of precoded GFDM: (i) Walsh Hadamard Transform; (ii) CAZAC transform and; (iii) Discrete Hartley Transform. The PAPR and symbol error rate of these three unitary transform combined with GFDM are analyzed as well.

The block diagonalization (BD) precoding technique is a well-known linear transmit strategy for multiuser multi-input multi-output (MU-MIMO) systems. The MU-MIMO broadcast channel is decomposed into multiple independent parallel single user MIMO (SU-MIMO) channels and achieves the maximum diversity order at high data rates. The lattice reduction-aided decoding (LRAD) features the reduced decoding complexity in MIMO communications. The Lenstra-Lenstra-Lovasz (LLL) algorithm has been extensively used to obtain better bases of the channel matrix while the complex lattice reduction (CLR) is aimed at improving orthogonality of basis vectors and shortening them. The orthogonalization and size reduction work are left for the CLR algorithm so that a modification of the channel matrix is carried out, resulting in better precoding and detection performances. We also derive bounds for lattice decoding. Simulation results show that the bit error rate (BER) performance of our proposed algorithm is better than that of conventional ones and it reduces the complexity compared with the LLL algorithm-based schemes.

The problems of redundant RFID reader detection and coverage have instigated researchers to propose different optimization heuristics due to the rapid advance of technologies in large-scale RFID systems. In this paper, we present a layered elimination optimization (LEO) which is an algorithm-independent technique aims to detect maximum amount of redundant readers that could be safely removed or turned off with preserving original RFID network coverage. A significant improvement of the LEO scheme is that amount of "write-to-tag" operations could be largely reduced during the redundant reader identification phase. Moreover, LEO is a distributed approach which does not need to collect global information for centralizing control, leading to no communications or synchronizations among RFID readers. To evaluate the performance of the proposed techniques, we have implemented the LEO technique along with other methods. Both theoretical analysis and experimental results show that the LEO is reliable, effective, and efficient. The proposed techniques can provide reliable performance with detecting higher redundancy and has lower algorithm overheads.