Massive MIMO systems have made significant progress in increasing spectral and energy efficiency over traditional MIMO systems by exploiting large antenna arrays. In this paper we consider the joint maximum likelihood (ML) channel estimation and data detection problem for massive SIMO (single input multiple output) wireless systems. Despite the large number of unknown channel coefficients for massive SIMO systems, we improve an algorithm to achieve the exact ML non-coherent data detection with a low expected complexity. We show that the expected computational complexity of this algorithm is linear in the number of receive antennas and polynomial in channel coherence time. Simulation results show the performance gain of the optimal non-coherent data detection with a low computational complexity.

Abstract-Massive MIMO communication systems, by virtue of utilizing very large number of antennas, have a potential to yield higher spectral and energy efficiency in comparison with the conventional MIMO systems. In this paper, we consider uplink channel estimation in massive MIMO-OFDM systems with frequency selective channels. With increased number of antennas, the channel estimation problem becomes very challenging as exceptionally large number of channel parameters have to be estimated. We propose an efficient distributed linear minimum mean square error (LMMSE) algorithm that can achieve near optimal channel estimates at very low complexity by exploiting the strong spatial correlations and symmetry of large antenna array elements. The proposed method involves solving a (fixed) reduced dimensional LMMSE problem at each antenna followed by a repetitive sharing of information through collaboration among neighboring antenna elements. To further enhance the channel estimates and/or reduce the number of reserved pilot tones, we propose a data-aided estimation technique that relies on finding a set of most reliable data carriers. We also analyse the effect of pilot contamination on the mean square error (MSE) performance of different channel estimation techniques. Unlike the conventional approaches, we use stochastic geometry to obtain analytical expression for interference variance (or power) across OFDM frequency tones and use it to derive the MSE expressions for different algorithms under both noise and pilot contaminated regimes. Simulation results validate our analysis and the near optimal MSE performance of proposed estimation algorithms.

The energy efficient resource allocation scheme based on genetic algorithm (GA) for the downlink orthogonal frequency division multiple access (OFDMA) heterogeneous networks (HetNets) is developed in this paper. To maximize the spectrum efficiency for the fifth generation (5G) mobile networks, frequency reuse-1 is employed. Thus, advanced inter-cell interference coordination techniques are required to mitigate the inter-cell interference for 5G HetNets. In this paper, the energy efficient optimization problem based on coordinated scheduling is formulated, which is a mixed-integer nonlinear fractional programming problem and is intractable to solve directly. To tackle this, a two-step GA based scheme is proposed to solve the optimization problem. In the first step, the resource blocks matrix is solved by normal GA in the spectral efficiency aspect with fixed power distribution matrix, and then the power distribution matrix is obtained in the second step by non-dominated sorting genetic algorithm II (NSGA-II) with obtained resource blocks allocation matrix. Finally, the system level numerical evaluation process is provided to illustrate the effectiveness of the developed scheme.INDEX TERMS Energy efficiency, resource allocation, heterogeneous networks, genetic algorithm.

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MIMO systems employing sphere decoding (SD) algorithm are known to achieve near maximum likelihood (ML) performance at a reduced complexity by restricting the candidate search space to a sphere of a certain radius. The performance of SD depends on the precise estimation of its soft output. In this paper, a low complexity modified Likelihood Ascent Search (LAS) algorithm is proposed to be used within a SD receiver in order to precisely estimate the counter-hypothesis for its winner candidates. The LAS algorithm is modified to search for the best counter-hypothesis in only one-half of the signal lattice thereby improving the performance of MIMO receiver. Our results challenge the popular perception that for a SD receiver a large number of candidates within the search sphere is essential for good performance. Instead, it is shown that accurate estimation of the counter-hypothesis is equally important and in fact, the performance of the proposed augmented SD receiver with only single candidate approaches that of a classical SD with multiple candidates. Bit error rate performance of the proposed method when compared with the existing research works on soft output generation for the same number of candidates shows that our proposed method outperforms them by upto 3 dB.

Abstract:In this paper, the impact of initial search radius on the complexity and performance of a sphere decoding algorithm is investigated for different user positions within a distributed antenna system. In a distributed antenna system, users can take up random positions within the cell clusters. The channel matrix can therefore take up infinitely different forms. In the presented work, a distributed antenna system with three different user positions in the cooperating cells is considered by employing different channel matrices. The effect on the complexity and performance of the sphere decoder due to the choice of the initial sphere radius is investigated for these user positions. It is shown that the signal lattice volume changes considerably for different user positions within the cells. A dynamic radius allocation algorithm is proposed in which the behavior is exploited by dynamically adjusting the initial sphere radius based on the knowledge of the channel path gain matrix. The simulation results show that the proposed algorithm results in a considerable reduction in the complexity of the sphere decoder in a distributed antenna system. Additionally, the performance of the sphere decoder in different coupling scenarios within the distributed antenna system has been investigated for a different number of candidates. It is shown that the performance of cell edge users can be considerably enhanced with high channel diversity, which otherwise could severely deteriorate the overall system performance.

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