Jingming Kuang

Performance Analysis and Location Optimization for Massive MIMO Systems With Circularly Distributed Antennas

We analyze the achievable rate of the uplink of a single-cell multi-user distributed massive multiple-input-multiple-output (MIMO) system. Each user is equipped with single antenna and the base station (BS) is equipped with a large number of distributed antennas. We derive an analytical expression for the asymptotic ergodic achievable rate of the system under zero-forcing (ZF) detector. In particular, we consider circular antenna array, where the distributed BS antennas are located evenly on a circle, and derive an analytical expression and closed-form bounds for the achievable rate of an arbitrarily located user. Subsequently, closed-form bounds on the average achievable rate per user are obtained under the assumption that the users are uniformly located. Based on the bounds, we can understand the behavior of the system rate with respect to different parameters and find the optimal location of the circular BS antenna array that maximizes the average rate. Numerical results are provided to assess our analytical results and examine the impact of the number and the location of the BS antennas, the transmit power, and the path-loss exponent on system performance. Simulations on multi-cell networks are also demonstrated. Our work shows that circularly distributed massive MIMO system largely outperforms centralized massive MIMO system.

A scheme of multi-user reusing one slot on enhancing capacity of GSM/EDGE networks

GSM network is seeing its greatest expansion because of the growing demand for mobile voice services in emerging markets recently. A newly proposed technology, multiuser reusing one slot (MUROS), would help operators in densely populated cities to alleviate the strain on their networks. The concept of MUROS is based on multiplexing two or more users onto one time slot without degrading the speech quality. We improved one solution of MUROS, orthogonal sub channel (OSC) in this contribution. For the downlink (DL) OSC, we designed new training sequence codes (TSCs) which are low cross-correlated with legacy TSCs. For the uplink (UL) OSC, we adopted successive interference cancellation based on minimum mean square error (MMSE-SIC) algorithm. Theoretical analysis and simulation results shows that with proper TSC design, OSC is a promising scheme of MUROS due to its ability to double the capacity of GSM/EDGE networks without degrading the speech quality very much.

The Application of EESM and MI-Based Link Quality Models for Rate Compatible LDPC Codes

System evaluation of different resource allocation, power control and link adaptation (LA) solutions require the multi-cell system simulations, which provide important reference to the standardization and system design. Such a system-level simulator is expected to be reliable and quick enough, which requires a very accurate and simple link quality model. The exponential effective-SNR mapping (EESM) model [1, 2] and mutual information-based (MI-based) model [3] were proposed recently, which have been proved to be pretty accurate and independent of fading for 3 GPP Turbo-coded orthogonal frequency division multiplexing (OFDM) system [3, 4]. This paper investigates the accuracies of the above two models for the low-density parity-check (LDPC) codes, in terms of veracity and complexity for different coding rates, block lengths, mobile speeds and modulation schemes. Simulation results verify that both methods show quite good performance in different multi-state channels. The simpler MI-based model performs even better. Especially its coding model is independent of modulation schemes.

Power allocation for OFDM-based cognitive heterogeneous networks

In this paper, the capacity maximization and the spectrum utilization efficiency improvement are investigated for the Pico cells in broadband heterogeneous networks. In frequency-reuse model, the users attached to Macro base station are usually viewed as primary users, and those attached to Pico base station should be regarded as cognitive radio (CR) users. As both the primary users and the CR users communicate in parallel frequency bands, the performance of the system is limited by the mutual inter-carrier interference (ICI). In order to control ICI and maximize the achievable transmission rate of the CR users, an effective power allocation scheme is proposed to maximize the transmission rate of the CR users under a given interference threshold prescribed by the primary users. By transforming this suboptimal solution into an innovative matrix expression, the algorithm is easier to perform in practice. The simulation results demonstrate that the proposed algorithm provides a large performance gain in Pico cell capacity over the non-cooperative and equal power allocation schemes.

Robust Coordinated Beamforming for Secure MISO Interference Channels with Bounded Ellipsoidal Uncertainties

This letter addresses the robust optimization problem of downlink coordinated beamforming over the multiple-input single-output (MISO) interference channel with confidential messages (IFC-CM) exploiting imperfect channel state information (CSI) at the transmitters. Our aim is to minimize the total transmitted power subject to the worst-case individual signal-to-interference-plus-noise-ratio (SINR) and equivocation rates. To model the imperfect CSI, bounded ellipsoidal uncertainties for channel vector and covariance are both considered. By deriving the equivalent forms for the SINR and secrecy constraints, the worst-case robust problem can be reformulated as a semi-definite programming (SDP) with the help of rank relaxation. Simulation results show the effectiveness of the proposed algorithm.

Robust transceiver design for AF MIMO relay systems with column correlations

In this paper, we investigate the robust transceiver design for dual-hop amplify-and-forward (AF) MIMO relay systems with Gaussian distributed channel estimation errors. Aiming at maximizing the mutual information under imperfect channel state information (CSI), source precoder at source and forwarding matrix at the relay are jointly optimized. Using some elegant attributes of matrix-monotone functions, the structures of the optimal solutions are derived first. Then based on the derived structure an iterative waterfilling solution is proposed. Several existing algorithms are shown to be special cases of the proposed solution. Finally, the effectiveness of the proposed robust design is demonstrated by simulation results.

Secrecy-Rate Balancing for Two-User MISO Interference Channels

This paper considers a two-user multiple-input single-output (MISO) interference channel with confidential messages (IFC-CM), where the beamforming vectors at the two transmitters are jointly optimized using the closed-form Pareto-optimal parameterization. We show that coordinated beamforming is secrecy-rate optimal which is achieved by agreeing on the parameters between the two transmitters. We first analyze the feasible set of the beamforming parameters that guarantees positiveness of the secrecy rates. We then derive a quadratic relationship that finds the Pareto-optimal parameters to achieve secrecy-rate balancing beamforming.

Low complexity list successive cancellation decoding of polar codes

The authors propose a low complexity list successive cancellation (LCLSC) decoding algorithm, where the advantages of the successive cancellation (SC) decoding and the list successive cancellation (LSC) decoding are both considered. In the proposed decoding, SC decoding instead of LSC decoding is implemented when all information bits from bad subchannels are received reliably. While the reliability of each information bit is estimated by its likelihood ratio (LR), the bit channel quality is measured via its Bhattacharyya parameter. To achieve this goal, the authors introduce two thresholds: LR threshold and Bhattacharyya parameter threshold. Also, the methods to determine them are both elaborated. The numerical results suggest that the complexity of LCLSC decoding is much lower than LSC decoding and can be close to that of SC decoding, while the error performance is almost equal to that of LSC decoding. Especially, when the code rate is in low region, the advantage of our decoding is more obvious.

Statistically robust resource allocation for distributed multi-carrier cooperative networks

In this paper, we investigate joint subcarrier and power allocation scheme for distributed multicarrier cooperative networks with imperfect channel state information. Using practical channel estimation algorithms, the statistic model of the channel estimation error is first derived. Then based on the channel error model, the resource allocation scheme aims at maximizing the sum rate of the overall network. Specifically, both subcarrier allocation and power allocation are taken into account. In the subcarrier allocation, a realistic problem of the power leakage between neighboring subcarriers is also addressed. Furthermore, based on Lagrange dual-decomposition algorithm, a practical power allocation algorithm is proposed. Finally, the simulation results demonstrate the performance advantages of the proposed robust design.

Design of Binary Network Codes for Multiuser Multiway Relay Networks

We study multiuser multiway relay networks where N user nodes exchange their information through a single-relay node. We use network coding (NC) in the relay to increase the throughput. Due to the limitation of complexity, we only consider the binary multiuser NC (BMNC) in the relay. We study the BMNC matrix [in GF(2)] and propose several design criteria on the BMNC matrix to improve the symbol error probability (SEP) performance. Closed-form expressions of the SEP of the system are provided. Moreover, an upper bound of the SEP is also proposed to provide further insights into system performance. Then, BMNC matrices are designed to minimize error probabilities.