In this paper, we address a joint design of symbol level beam selection and precoding in the multi-user downlink beamspace multiple-input single-output (MISO) system. Unlike the general concept of eliminating or avoiding inter-user interference, the symbol level design aims to exploit the constructive interference at symbol level among the multiple users. To optimize the constructive interference while ensuring the signal interference noise ratio (SINR), a cardinality constrained minimum mean square error (MMSE) problem with per-beam power limitation is formulated. To resolve this non-convex and non-smooth problem, we propose a penalty proximal alternating linearized minimization based algorithm, in which a sequence of penalty sub-problems are solved by iteratively executing two projections: selective constructive signal region projection and sparse beam selection projection. From the extensive simulation results, the convergence of the proposed algorithm and its effectiveness are demonstrated.

Polar code is adapted as the channel coding scheme for control channel in 5G NR. The basic algorithm of polar code is the successive cancelation (SC) decoding but its performance is not good enough and decoding latency is relatively high. So the simplified successive cancelation list(SSCL) decoding is generally used. When the SSCL is operated, path metric calculator generates children candidates and the number of children candidates influenced on the H/W complexity. The reliability of children candidates is affected by that of their parent candidates. The number of children candidates is adaptively selected according to the reliability of their parent candidate and the total number of children candidates could be reduced. Our proposed algorithm reduces H/W complexity of polar decoder while preserving decoding performance.

Due to the short wavelength of mmWave channel in 5G, the size of antenna array becomes reduced and beamforming has been thus adopted in mobile handsets. To enable the beamforming, the phase shifter is necessary to control the phases from different antenna elements. However the phase shifter can have non-ideal phase and non-identical gain responses over the antenna elements and phase codes. To consider such impairments in practice, we suggest the code search algorithm using low-complexity measurement for desired beam directions and its applications in beam codebook generation. Using the numerical simulation, it is shown that the spherical coverage can be improved by the proposed procedure using the combination of modelling and measurements.

In this paper, a supervised-learning based blind detection of interference parameters for network-assisted interference cancellation and suppression (NAICS) system is proposed. In order to enable joint detection or interference cancellation at a user equipment in NAICS system, we consider detection of the interference parameters including traffic-to-pilot power ratio (TPR), rank indicator (RI), and precoding matrix indicator (PMI). We divide overall process for detection of these interference parameters into two steps, and propose supervised learning based neural network architecture for detection of corresponding parameters in each steps. Link-level simulation results are provided to validate detection performance of the proposed neural network architecture and performance of NAICS system which uses the proposed learning based detection method with respect to block error rate (BLER).

The exponential growth of data rate in advanced wireless communication systems results in an overwhelming overhead on physical links that transport complex-value digital signal between Radio Frequency (RF) unit and Baseband Processor (BBP) at mobile terminal. To suppress this overhead, we present the data compression which lowers the bit-width of inphase (I) and quadrature(Q) sample to be transferred over RF-BBP link. The proposed compression schemes are based on floating-point transform and bit-level modification targeting for orthogonal frequency division multiplexing (OFDM) signal in Long Term Evolution (LTE) and New Radio (NR) systems, which lead to cost-effective implementation with a low latency and reduced computational complexity. Through theoretical analysis and performance evaluation, it is verified that the intended data rate using 4 × 4 MIMO and 256QAM is achieved with an ignorable performance loss compared to the uncompressed mode, providing 25% compression ratio.

We propose a high-resolution hierarchical beam alignment algorithm that learns millimeter wave channel space using segmented beams obtained from feasible phase shifted sum of given hierarchical basis. To be specific, at each stage, the segmented beam is designed using a linear combination of given training beam basis instead of just choosing a beam among them. Then, the designed beam is used to determine the subset of higher resolution training beam candidates for the next stage which is referred to as the over-complete dictionary embracing even partially overlapped beams as elements. At the next stage, the proposed beam alignment can focus only on the most promising directions associated with finer grids. The simulation results demonstrate that the proposed beam alignment framework can remedy the limitations of the existing grid-of-beams method and achieve favorable beam alignment performance with reduced training time.

This paper investigates high rate systematic punctured convolutional codes based on Forney's (1970) results. High rate systematic punctured convolutional codes of rate-2/3 with constraint length 3/spl les/K/spl les/7 and rate-3/4 through 15/16 with K=7 are derived using the rate-1/2 best known nonsystematic convolutional codes. Weight spectra of newly discovered systematic punctured convolutional codes are provided and compared with the best known nonsystematic punctured codes. Simulation results on bit-error probabilities (BEPs) are also given.

We investigate the undetected error probabilities for bounded-distance decoding of binary primitive BCH codes when they are used for both error correction and detection on a binary symmetric channel. We show that the undetected error probability of binary linear codes can be simplified and quantified if the weight distribution of the code is binomial-like. We obtain bounds on the undetected error probability of binary primitive BCH codes by applying the result to the code and show that the bounds are quantified by the deviation factor of the true weight distribution from the binomial-like weight distribution.