Aiming at the load balancing problem for uneven traffic demands among different beams in a broadband multibeam satellite network (BMSN), we present a mathematical analysis and propose a load balancing algorithm to improve the efficiency of system resource allocation. In contrast to existing studies, our research focuses on the heterogeneous real-time services, including both VoIP and MPEG traffic flows. Subject to the delay constraint of real-time traffic, we introduce a QoS guaranteed resource scheduling framework for each beam. Based on this framework, we simulate the load imbalance scenario through the Poisson random point process. Then, we present joint adjacent beams and hopping beams load balancing algorithm to maintain the better match between the system resource and uneven traffic demands for BMSN over the satellite lifetime. The key point of our algorithm is intended to reduce the packet loss ratio (PLR) for each user and improve the BMSN's throughput. Simulation results show that the proposed load balancing algorithm can effectively reduce the average packet loss ratio of all beams by 71.25% and improve the average throughput of all beams by 13.97%.

Processor architects usually design uniprocessor or chip multiprocessor (CMP) by using a platform-based approach. One of the major challenges in this approach is to explore the exponential-size design space composed of many tunable and interacting architectural parameters. An exhaustive search of the design space is prohibitive because of the expensive run-time of simulations. So an efficient design space exploration (DSE) strategy that can fast find the multi-objective architectural configurations (points in design space) in terms of system metrics like performance and energy is needed. In this paper, we propose an accurate and efficient adaptive component selection and smoothing operator (ACOSSO) metamodel assisted NSGA-II (MA-NSGA-II) multi-objective optimization (MOO) technique for processor DSE. We show the effectiveness of our methodology by comparing with linear regression (LR), restrict cubic splines (RCS), natural cubic splines (NCS) and artificial neural network (ANN) metamodeling techniques for processor design metrics prediction and architecture optimization. The experimental results show that, the proposed methodology achieves higher prediction accuracy and better architecture optimization results.

High-order QAM modulation schemes are recommended in various communication systems. However, soft demodulating a high-order QAM constellation is complicated when applying traditional methods. In this paper, a novel de-mapper is proposed based on the fact that the clipped LLR can also offer sufficient soft-information, meanwhile the theoretical LLR curves are approximately linear in this clipped range. Hence a first-order linear function is designed to approximate the theoretical value. Simulation results and complexity analysis demonstrate that the proposed de-mapper outperforms traditional approaches in terms of BER performance, and also keeps low complexity.

A parallelized generation of Zadoff-Chu (ZC) and the Discrete Fourier Transform of Zadoff-Chu (ZC-DFT) sequences is proposed. In this algorithm, the sampling operation is completely eliminated for the ZC-DFT sequences generation. Implemented on a vector Digital Signal Processor (DSP), the proposed algorithm makes an efficient use of the parallel DSP structure and achieves a high computing speed, owing to the decomposition of the root index. Since only a few “seed sequences” are required, the proposed algorithm obtains an extremely low memory requirement and a high precision.

“Small Cell” is regarded as the solution to optimize 4G wireless networks with improved coverage and capacity and expected to be deploy in a large number. To meet performance requirements and special constraints on the cost and size, we design a heterogeneous multi-processor SoC for small cell base station, which is composed of ASP (Application Specific Processor) cores, hardware accelerators, general-purpose processor core, and infrastructure and interface blocks. The challenges of developing such a complex chip drive us to employ system-level design methodology in both single core and mutli-core architecture optimizations. The paper discusses in detail the LISA (Language for Instruction-Set Architectures)/SystemC based ASP-algorithm joint optimization, and task-graph driven multi-core architecture exploration. Finally, the results of silicon implementation on SMIC 55nm technology are presented.

In this paper, we present a sparse channel estimation method for orthogonal frequency division multiplexing (OFDM) based two-way relay networks (TWRN). Conventional channel estimation methods, such as least squares (LS), have been proposed to obtain channel state information (CSI) at the cost of the training resource, which reduce spectrum efficiency. However, physical measurements have verified that the wireless channels tend to exhibit sparse structures in high-dimensional spaces, e.g., delay spread, Doppler spread and space spread. With the development of compressive sensing (CS), a novel compressive channel estimation method which is called adaptive compressive matching pursuit (ACMP) algorithm is proposed by using the sparse constraint between the terminal nodes and the relay node in the TWRN. Simulation results confirm that ACMP channel estimation method provides significant improvement in mean square error (MSE) performance compared to the conventional channel estimation methods.

This paper presents an ASP (application specific processor) with 512-bit SIMD (Single Instruction Multiple Data) and 192-bit VLIW (Very Long Instruction Word) architecture optimized for wireless baseband processing. It employs optimized architecture and address generation unit to accelerate the kernel algorithms. Based on the ASP, a multi-core baseband processor is developed which can work at 2×2 MIMO and 20 MHz physical bandwidth configuration for LTE inner receiver and meet requirements of Category 3 User Equipment (CAT3 UE). Furthermore, a silicon implementation of the baseband processor with 130nm CMOS technology is presented. Experimental results show that the baseband processor provides 100 GOPS computing ability at 117.6MHz.

In LTE uplink, a DFT with 34 possible lengths is performed. The traditional method directly transforms the sequences with different lengths by using the mixed-radix FFT which is not appropriate to apply on the DSP processor only supplying radix-2 butterfly hardware especially. In this paper, we resample the arbitrary-length input sequence so that a 2n-point FFT can be applied by using the polyphase filter. Theoretical analysis demonstrates the equivalence of the proposed polyphase-filter-based FFT (PF-FFT) and the original DFT. Moreover, the PF-FFT also keeps low complexity and good fixed-point performance.

The authors consider the robust Tomlinson–Harashima precoding (THP) for downlink multiuser multiple-input multiple-output orthogonal frequency-division multiplexing systems with quantised feedback. The authors discuss vector channel feedback strategies in the frequency and time domains, and develop a robust version of THP that takes into account of error statistics of the channel state information, that consists of the optimal feedforward filters, feedback filters and the receive filters. Feedback techniques are developed to exploit the spatial correlations in realistic 3GPP channel models by applying dimension reduction and scalar-quantisation. Extensive simulations results are provided to demonstrate the performance of the proposed robust THP design as well as the channel feedback scheme.

An efficient hardware-optimized Physical Random Access Channel (PRACH) baseband signal generation algorithm and its ASIC implementation in the LTE user equipment (UE) transmitter are presented in this paper. A simplified DFT of the Zadoff-Chu (ZC) sequence as well as a phase computation are applied to the prime size DFT of the PRACH preamble and the large size IDFT is accomplished by groups of smaller size IFFTs. The optimized algorithm achieves significantly lower computational complexity compared with the original algorithm in the LTE specification and better performance compared to another publication. The ASIC architecture is also designed to reduce the memory size and logic complexity, which achieves a low hardware cost in terms of the cell area. The proposed design was implemented in 65nm CMOS and it was demonstrated that this design can satisfy the timing requirements of the LTE specification.

We consider the robust linear precoding (LP) and Tomlinson-Harashima precoding (THP) schemes for multiuser MIMO-OFDM downlink channels with limited feedback. Benefiting from the correlation of spatial channels, the mobile terminal compresses and feeds back the time-domain channel vectors instead of the corresponding frequency-domain vectors to substantially reduce the feedback signalling overhead. A compression and restoration method and a codebook design for channel state information at the transmitter (CSIT) feedback are proposed in the time domain. By treating the partial CSIT as a random quantity, we develop the robust precoders to combat the truncation and quantization errors introduced in the feedback procedure. In comparison with the non-robust designs, both the robust LP and THP have better bit-error rate performance especially in high signal-to-noise ratio region.

This letter proposes a blind carrier frequency offset (CFO) estimator for orthogonal frequency-division multiplexing (OFDM) systems based on the frequency analysis of the received signal, and derives a closed-form CFO estimate. Since only one OFDM symbol is utilized instead of multi-symbol averaging, the proposed method is effective even when the CFO is time varying. Finally, analysis and simulation results indicate the outstanding performance of the proposed estimator.

Carrier frequency offset (CFO) estimation is a critical problem in orthogonal frequency-division multiplexing (OFDM) systems. This letter proposes a blind CFO estimator based on smoothing the signal power spectrum. A closed-form CFO estimate is also presented, which greatly reduces the computational complexity of the proposed method. Analysis and simulation results show that the proposed estimator is very effective for OFDM systems.

A successive interference cancellation (SIC) algorithm based on breadth-first search (BFS) is developed to achieve a soft-input soft-output detector via the tree structure of the MIMO system model in this paper. Instead of visiting all nodes of the tree, the proposed BFS-SIC algorithm only browses and extends those paths with large metrics. If paths are enough, the performance of BFS-SIC algorithm can approach that of sphere decoding but is much more flexible due to its providing a good tradeoff between complexity and performance. Moreover, the BFS-SIC algorithm possesses path metrics including only scalar operations rather than matrix operations. Simulation results demonstrate the effectiveness of the proposed algorithm.

A novel oblique projection based detection scheme is proposed to reduce the computational cost of the vertical Bell Laboratories Layered Space-Time (V-BLAST) receivers. It constructs the ordinary zero-forcing (ZF) and minimum mean- square error (MMSE) detectors by oblique projector implementation, and has a computationally efficient way via projection matrix recursion. Different from the existing ones, we design a so-called "inverse" detection order to facilitate this new approach, whose complexity compares favorably with the competing alternatives. Theoretical analysis and simulation results show the efficiency of the proposed algorithm.

For code division multiple access (CDMA) systems operating over dispersive channels, the nested recursive least-squares (RLS)-type algorithm, based on minimum output energy (MOE) criterion, attracts much attention as an efficient interference suppression scheme for its simple adaptive recursion. In this letter, we investigate its performance analysis. Special attention is paid to theoretical issues concerning the global convergence and convergence dynamics performance. It is shown that this algorithm exhibits a global minimum attained, and the convergence is immune to the eigenvalue spread of the correlation matrix of received signal vector. Simulation results demonstrate that the nested RLS-type algorithm has indeed the expected convergence performance