In this paper, a nonlinear quantized precoding scheme for low-resolution digital-analog converters (DACs) in a massive multiple-input multiple-output (MIMO) system is proposed. The nonlinear quantized precoding determines transmit antenna outputs with a transmit symbol and channel state information. In a full-digital massive MIMO system, low-resolution DACs are used to suppress power consumption. Conventional precoding algorithms for low-resolution DACs do not optimize transmit antenna gains individually. Thus, in this paper, a precoding scheme that optimizes individual transmit antenna gains as well as the DAC outputs is proposed. In the proposed scheme, the subarray of massive MIMO antennas is treated virtually as a single antenna element. Numerical results obtained through computer simulation show that the proposed precoding scheme achieves bit error rate performance close to that of the conventional precoding scheme with much smaller antenna gains on a CDL-A channel.

In this paper, a non-linear precoding algorithm with low out-of-band (OOB) radiation is proposed for massive multiple-input multiple-output (MIMO) systems. Massive MIMO sets more than one hundred antennas at each base station to achieve higher spectral efficiency and throughput. Full digital massive MIMO may constrain the resolution of digital-to-analog converters (DACs) since each DAC consumes a large amount of power. In massive MIMO systems with low resolution DACs, designing methods of DAC output signals by nonlinear processing are being investigated. The conventional scheme focuses only on a sum rate or errors in the received signals and so triggers large OOB radiation. This paper proposes an optimization criterion that takes OOB radiation power into account. Gibbs sampling is used as an algorithm to find sub-optimal solutions given this criterion. Numerical results obtained through computer simulation show that the proposed criterion reduces mean OOB radiation power by a factor of 10 as compared with the conventional criterion. The proposed criterion also reduces OOB radiation while increasing the average sum rate by optimizing the weight factor for the OOB radiation. As a result, the proposed criterion achieves approximately 1.3 times higher average sum rates than an error-based criterion. On the other hand, as compared with a sum rate based criterion, the throughput on each subcarrier shows less variation which reduces the number of link adaptation options needed although the average sum rate of the proposed criterion is smaller.

This paper proposes relay selection techniques for XOR physical layer network coding with MMSE based non-linear precoding in MIMO bi-directional wireless relaying networks. The proposed selection techniques are derived on the different assumption about characteristics of the MMSE based non-linear precoding in the wireless network. We show that the signal to noise power ratio (SNR) is dependent on the product of all the eigenvalues in the channels from the terminals to relays. This paper shows that the best selection techniques in all the proposed techniques is to select a group of the relays that maximizes the product. Therefore, the selection technique is called “product of all eigenvalues (PAE)” in this paper. The performance of the proposed relay selection techniques is evaluated in a MIMO bi-directional wireless relaying network where two terminals with 2 antennas exchange their information via relays. When the PAE is applied to select a group of the 2 relays out of the 10 relays where an antenna is placed, the PAE attains a gain of more than 13dB at the BER of 10-3.

This paper proposes coded modulation for physical layer network coding in multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) bi-directional wireless relay systems where precoding is applied. The proposed coded modulation enables the relays to decode the received signals, which improves the transmission performance. Soft input decoding for the proposed coded modulation is proposed. Furthermore, we propose two precoder weight optimization techniques, called “per subcarrier weight optimization” and “total weight optimization”. This paper shows a precoder configuration based on the optimization with the lattice reduction or the sorted QR-decomposition. The performance of the proposed network coding is evaluated by computer simulation in a MIMO-OFDM two-hop wireless relay system with the 16 quadrature amplitude modulation (QAM) or the 256QAM. The proposed coded modulation attains a coding gain of about 2dB at the BER of 10-4. The total weight optimization achieves about 1dB better BER performance than the other at the BER of 10-4.

This paper proposes an XOR physical layer network coding (XOR-PLNC) with non-linear precoding for quadrature amplitude modulations (QAMs) in bi-directional MIMO relay systems. The proposed XOR-PLNC applies power loading in order to improve the transmission performance. The proposed XOR-PLNC introduces a modulus adapted to channel gains. Moreover, the modulus is further reduced in cooperation with modulo operation which the non-linear precoding employs for improvement of transmission power efficiency. The use of the reduced modulus improves the energy efficiency of the signal transmission, which improves the transmission performance in the proposed XOR-PLNC. The performance is evaluated by computer simulations in bi-directional MIMO relay channels with 16QAM to 1024QAM.

Non-linear precoding (NLP) scheme for downlink multi-user multiple-input multiple-output (DL-MU-MIMO) transmission has received much attention as a promising technology to achieve high capacity within the limited bandwidths available to radio access systems. In order to minimize the required transmission power for DL-MU-MIMO and achieve high spectrum efficiency, Vector Perturbation (VP) was proposed as an optimal NLP scheme. Unfortunately, the original VP suffers from significant computation complexity in detecting the optimal perturbation vector from an infinite number of the candidates. To reduce the complexity with near transmission performance of VP, several recent studies investigated various efficient NLP schemes based on the concept of Tomlinson-Harashima precoding (THP) that applies successive pre-cancellation of inter-user interference (IUI) and offsets the transmission vector based on a modulo operation. In order to attain transmission performance improvement over the original THP, a previous work proposed Minimum Mean Square Error based THP (MMSE-THP) employing IUI successive pre-cancellation based on MMSE criteria. On the other hand, to improve the transmission performance of MMSE-THP, other previous works proposed Ordered MMSE-THP and Lattice-Reduction-Aided MMSE-THP (LRA MMSE-THP). This paper investigates the further transmission performance improvement of Ordered MMSE-THP and LRA MMSE-THP. This paper starts by proposing an extension of MMSE-THP employing a perturbation vector search (PVS), called PVS MMSE-THP as a novel NLP scheme, where the modulo operation is substituted by PVS and a subtraction operation from the transmit signal vector. Then, it introduces an efficient search algorithm of appropriate perturbation vector based on a depth-first branch-and-bound search for PVS MMSE-THP. Next, it also evaluates the transmission performance of PVS MMSE-THP with the appropriate perturbation vector detected by the efficient search algorithm. Computer simulations quantitatively clarify that PVS MMSE-THP achieves better transmission performance than the conventional NLP schemes. Moreover, it also clarifies that PVS MMSE-THP increases the effect of required transmission power reduction with the number of transmit antennas compared to the conventional NLP schemes.

This paper proposes novel nonlinear precoding for XOR-physical layer network coding (XOR-PNC) to improve the performance of bi-directional MIMO relay systems. The proposed precoder comprises a pre-equalizer and a nonlinear filter, which we also propose in the paper. We theoretically analyze the performance of the XOR-PNC with the proposed nonlinear precoding. As a result, it is shown that the proposed pre-equalizer improves the distribution of the received signals at relays, while the nonlinear precoder not only improves the transmission power efficiency but also simplifies the receiver at the relays. The performance is confirmed by computer simulation. The XOR-PNC with the proposed precoding achieves almost the lower bound in BER performance, which is much better than the amplify-and-forward physical layer network coding (AF-PNC).

This study analyzes the performance of a downlink beamformer with partitioned vector quantization under optimized feedback budget allocation. A multiuser multiple-input single-output downlink precoding system with perfect channel state information at mobile stations is considered. The number of feedback bits allocated to the channel quality indicator (CQI) and the channel direction indicator (CDI) corresponding to each partition are optimized by exploiting the quantization mean square error. In addition, the effects of equal and unequal partitioning on codebook memory and system capacity are studied and elucidated through simulations. The results show that with optimized CQI-CDI allocation, the feedback budget distributions of equal or unequal partitions are proportional to the size ratios of the partitioned subvectors. Furthermore, it is observed that for large-sized partitions, the ratio of optimal CDI to CQI is much higher than that for small-sized partitions.

This paper considers coordinated linear precoding for rate optimization in downlink multicell, multiuser orthogonal frequency-division multiple access networks. We focus on two different design criteria. In the first, the weighted sum-rate is maximized under transmit power constraints per base station. In the second, we minimize the total transmit power satisfying the signal-to-interference-plus-noise-ratio constraints of the subcarriers per cell. Both problems are solved using standard conic optimization packages. A less complex, fast, and provably convergent algorithm that maximizes the weighted sum-rate with per-cell transmit power constraints is formulated. We approximate the non-convex weighted sum-rate maximization (WSRM) problem with a solvable convex form by means of a sequential parametric convex approximation approach. The second-order cone formulations of an objective function and the constraints of the optimization problem are derived through a proper change of variables, first-order linear approximation, and hyperbolic constraints transformation. This algorithm converges to the suboptimal solution while taking fewer iterations in comparison to other known iterative WSRM algorithms. Numerical results are presented to demonstrate the effectiveness and superiority of the proposed algorithm.

In this paper, we propose a modified Tomlinson Harashima precoding (THP) method with less increase of computational complexity for the multi-user MIMO downlink system. The proposed THP scheme minimizes the influence of noise enhancement at the receivers by placing the diagonal weighted filters at both transmitter side and receiver side with square root. Compared to previously proposed non-linear precoding methods including vector perturbation (VP), the proposed THP achieves high BER performance. Furthermore, we show that the proposed THP method is implemented with lower computational complexity than that of existing modified THP and VP in literature.

Precoding is an excellent choice for complementing the MIMO systems. Linear precoding techniques offer better performance at low signal-to-noise ratios (SNRs) while non-linear techniques perform better at higher SNRs. In addition, the non-linear techniques can achieve near optimal capacity at the expense of reasonable levels of complexity. However, precoding depends on the knowledge of the wireless channel. Recent work on MIMO systems have shown that channel-knowledge at the transmitter, in either full or partial forms, can increase the channel capacity and system performance considerably. Therefore, hybrid techniques should be deployed in order to obtain a better trade-off in terms of complexity and performance. In this paper, we present a hybrid precoding technique which deals with the condition of partial channel-knowledge while offering robustness against the effects of correlation and poorly scattered channels while at the same time keeping low levels of complexity and high performance.

In this paper, we present a transmission scheme for a multiple-input multiple-output (MIMO) quasi-static fading channel with imperfect channel state information at the transmitter (CSIT). In this scheme, we develop a precoder structure to exploit the available CSIT and apply spatial coupling for further performance enhancement. We derive an analytical evaluation method based on extrinsic information transfer (EXIT) functions, which provides convenience for our precoder design. Furthermore, we observe an area property indicating that, for a spatially coupled system, the iterative receiver can perform error-free decoding even the original uncoupled system has multiple fixed points in its EXIT chart. This observation implies that spatial coupling is useful to alleviate the uncertainty in CSIT which causes difficulty in designing LDPC code based on the EXIT curve matching technique. Numerical results are presented, showing an excellent performance of the proposed scheme in MIMO fading channels with imperfect CSIT.

We study the transmission techniques in orthogonal frequency division multiplexing (OFDM) systems with imperfect channel state information at the transmitter (CSIT). We focus on the issue of utilizing the available CSIT by a single forward error control (FEC) code. We first analyze the system performance for the ideal coding case. We then develop a simple but efficient scheme for the practical coding case, which is based on joint FEC coding and linear precoding at the transmitter and iterative linear minimum-mean-square-error (LMMSE) detection at the receiver. Numerical results show that significant performances gains can be achieved by the proposed scheme.

A major drawback with linear precoding in a downlink multi-user MIMO system is the increase in the transmit power when a channel is correlated. On the other hand, nonlinear trellis precoding in downlink multi-user MIMO systems is capable of minimizing the transmit power by adding a shaping sequence to the original transmit sequence. However, conventional trellis precoding cannot be directly applied to existing bit-interleaved coded MIMO-OFDM systems since the trellis precoding and error correcting codes should be designed separately. In this paper, we proposed to embed trellis precoding into the error correcting codes that are used in the original multi-user MIMO-OFDM system employing linear precoding. Major advantage of this approach is that the receiving procedure at user terminals designed for the original system need not be changed up to the error correcting decoder to support our trellis precoding. Computer simulations show that the proposed trellis precoding provides improvements of 2 dB and 2.5 dB in 22 and 33 MIMO configurations, respectively.

For unitary space-time code (USTC), the impact of spatial correlation on error performance is investigated. A tighter and simpler upper bound is derived for generalized likelihood ratio test decoder. We establish that the spatial correlation does not change the diversity gain, whereas it degrades the error performance of USTC. Motivated by the precoding of space-time block code, we designed a precoder for USTC to handle the case of the joint transmit-receive correlation. Numerical results show that the degradation in performance due to spatial correlation can be considerably compensated by the proposed algorithm.

An improved signal-to-jamming and noise ratio (SJNR) method is proposed for the linear precoding of multiuser MIMO downlink systems. To well balance suppression of co-channel interference and suppression of noise, the proposed method modifies the noise variance term to argument of a piecewise linear function, and then enhances the suppression of noise. A dynamic power allocation scheme is also introduced to further decrease the overall average bit error rate of the system. Simulation results prove the effectiveness of the proposed scheme.

A powerful HARQ-based linear precoding scheme is proposed to utilize the flexibility of post-combining HARQ strategy in MIMO communications systems. The scheme selects the appropriate symbols and transmit powers for each eigen-mode to acquire more performance gains. Simulation results show that the proposed scheme achieves about 5.5 dB signal-to-noise ratio gains over original spatial multiplexing scheme at an average bit error rate of 10-4. Furthermore, the gap between the two schemes increases with the number of transmissions.

This letter proposed a linear precoding scheme for the V-BLAST system that requires only knowledge of the statistical CSI; the transmitter does not need the instantaneous CSI. Power allocation on the eigenmodes of the transmit correlation matrix is one way to minimize bit error rate (BER). Simulation results show that the proposed precoding V-BLAST system provides a significant reduction in the BER compared with the conventional V-BLAST systems.