In this paper, we design the precoding matrix with broad coverage for massive multi-input multi-output public channels. In order to guarantee the efficient use of power amplifiers and improve the achievable ergodic rate, equal transmit power per-antenna and semi-unitary constraints on the precoding matrix are considered simultaneously. Within the framework of manifold optimization, the precoding matrix design under the above two constraints becomes an optimization problem over the intersection of the oblique manifold and the Stiefel manifold. We propose to use the steepest descent method on the intersection of these two manifolds to obtain the optimal solution. By using the alternating projections method, the search direction of the steepest descent method is derived. Meanwhile, the convergence analysis for the proposed approach is also provided. The proposed approach can be used for both omnidirectional and sector-shaped power pattern design. Simulation results show that the power pattern of our designed precoder has less variation in different spatial directions within the cell coverage compared with the existing Zadoff-Chu scheme.

In this paper, we design the precoding matrix with broad coverage for massive multi-input multi-output (MIMO) public channels. To sufficiently utilize the power amplifier (PA) capacity of the base station (BS), all the rows of the precoding matrix should have the same 2-norm to guarantee equal transmit power on each antenna. In the meanwhile, the precoding matrix is semi-unitary, which can maximize the achievable ergodic rate for the independent and identically distributed (i.i.d.) channel. Within the framework of manifold optimization, the precoding matrix design under the above two constraints becomes an optimization problem over the intersection of the oblique manifold and the Stiefel manifold. We propose to use the steepest descent method on the intersection of these two manifolds to obtain the optimal solution. By using the alternating projections method, the search direction of the steepest descent method is derived. In the meanwhile, the convergence analysis for the proposed approach is also provided. Simulation results show that the power pattern of our designed precoder has less variation in different spatial directions within the cell compared with the existing schemes.

An efficient algorithm is developed to calculate the periodic steady-state distribution and moments of the remaining workload Wy at time yc within a cycle of length c, 0 ≤ y < 1, in a single-server queue with a periodic arrival-rate function. The algorithm applies exactly to the GIt/GI/1 model, where the arrival process is a time-transformation of a renewal process. A new representation of Wy makes it possible to apply a modification of the classic rare-event simulation for the stationary GI/GI/1 model exploiting importance sampling using an exponential change of measure. We establish bounds between the periodic workload and the stationary workload with the average arrival rate that enable us to prove that the relative error in estimates of P(Wy > b) is uniformly bounded in b. With the aid of a recent heavy-traffic limit theorem, the algorithm also applies to compute the periodic steady-state distribution of (i) reflected periodic Brownian motion (RPBM) by considering appropriately scaled GIt/GI/1 models and (ii) a large class of general Gt/G/1 queues by approximating by GIt/GI/1 models with the same heavy-traffic limit. Simulation examples demonstrate the accuracy and efficiency of the algorithm for both GIt/GI/1 queues and RPBM. The online supplement is available at https://doi.org/10.1287/ijoc.2017.0766 .

We propose beam division multiple access (BDMA) with per-beam synchronization (PBS) in time and frequency for wideband massive multiple-input multiple-output (MIMO) transmission over millimeter-wave (mmW)/Terahertz (THz) channels. Based on a physically motivated beam domain channel model, we first show that the envelopes of the beam domain channel elements tend to be independent of time and frequency when both the numbers of antennas at base station and user terminals (UTs) tend to infinity. Motivated by this, we then propose PBS for massive MIMO. We show that both the effective delay and Doppler frequency spreads of massive MIMO channels with PBS are reduced by a factor of the number of UT antennas compared with the conventional synchronization approaches. Subsequently, we apply PBS to BDMA and investigate beam scheduling to maximize the achievable ergodic rates for BDMA. Simulation results verify the effectiveness of BDMA with PBS for mmW/THz massive MIMO in typical mobility scenarios.

We propose beam division multiple access (BDMA) with per-beam synchronization (PBS) in time and frequency for wideband massive multiple-input multiple-output (MIMO) transmission over millimeter-wave (mmW)/Terahertz (THz) bands. We first introduce a physically motivated beam domain channel model for massive MIMO and demonstrate that the envelopes of the beam domain channel elements tend to be independent of time and frequency when both the numbers of antennas at base station and user terminals (UTs) tend to infinity. Motivated by the derived beam domain channel properties, we then propose PBS for mmW/THz massive MIMO. We show that both the effective delay and Doppler frequency spreads of wideband massive MIMO channels with PBS are reduced by a factor of the number of UT antennas compared with the conventional synchronization approaches. Subsequently, we apply PBS to BDMA, investigate beam scheduling to maximize the ergodic achievable rates for both uplink and downlink BDMA, and develop a greedy beam scheduling algorithm. Simulation results verify the effectiveness of BDMA with PBS for mmW/THz wideband massive MIMO systems in typical mobility scenarios.

We propose pilot reuse (PR) in single cell for massive multiuser multiple-input multiple-output (MIMO) transmission to reduce the pilot overhead. For spatially correlated Rayleigh fading channels, we establish a relationship between channel spatial correlations and channel power angle spectrum when the base station antenna number tends to infinity. With this channel model, we show that sum mean square error (MSE) of channel estimation can be minimized provided that channel angle of arrival intervals of the user terminals reusing the pilots are non-overlapping, which shows feasibility of PR over spatially correlated massive MIMO channels with constrained channel angular spreads. Since channel estimation performance might degrade due to PR, we also develop the closed-form robust multiuser uplink receiver and downlink precoder that minimize sum MSE of signal detection, and reveal a duality between them. Subsequently, we investigate pilot scheduling, which determines the PR pattern, under two minimum MSE related criteria, and propose a low complexity pilot scheduling algorithm, which relies on the channel statistics only. Simulation results show that the proposed PR scheme provides significant performance gains over the conventional orthogonal training scheme in terms of net spectral efficiency.

We propose pilot reuse (PR) in single cell for massive multiuser multiple-input multiple-output (MIMO) transmission to reduce the pilot overhead. For the spatially correlated Rayleigh fading channels, we establish a relationship between the channel spatial correlations and the channel power angle spectrum when the base station antenna number tends to infinity. With this channel model, we first show that the sum mean square error of the channel estimation (MSE-CE) can be minimized if the channel angle of arrival intervals of the user terminals reusing the pilots are non-overlapping, which shows the feasibility of PR in massive MIMO channels with constrained channel angular spreads. Then we design the pilot scheduler under the minimum MSE-CE criterion. With the channel estimation error due to PR taken into account, we also develop the closed-form robust uplink receiver and downlink precoder that minimize the sum MSE of the signal detection. Simulation results show that the proposed PR scheme provides significant performance gains over the conventional orthogonal training scheme in terms of the net spectral efficiency.

Classical connected components labelling algorithms are unsuitable for real-time processing of streamed images on an FPGA because they require two passes through the image. The basic requirements of connected components analysis are investigated, and this led to a novel single-pass approach that avoids the need to buffer an intermediate image. This is further analysed to give an algorithm that is both memory efficient and has the minimum latency. The final algorithm reduces the memory by over 300 times, and reduces the latency by more than a factor of 2.

Classical connected components labelling algorithms are unsuitable for real-time processing of streamed images on an FPGA because they require two passes through the image. Recently, a single-pass algorithm was proposed that avoided the need to buffer an intermediate image. In this paper, a new single pass algorithm is described that is a considerable improvement over the existing algorithms. The new algorithm reassigns and reuses labels each row to minimise the size of both the equivalence and region data tables. The optimised single-pass algorithm reduces the worst case memory requirement by over 100 times that of the original algorithm (for measuring region area), and reduces the latency to only 1 row.

Multiple input multiple output (MIMO) is the key techniques to achieve high throughput for 3GPP long term evaluation (LTE). In the downlink, the number of the receive antennas is limited by the weight, size and battery consumption requirements of the mobile terminal. Using multiple receive antennas will obviously be a limiting factor in the development of small terminals. In this paper, we propose a spatial temporal turbo channel coding scheme for 3GPP LTE to achieve both high data rate and performance. The advantage of the technique is that it is effective with a small number of receive antennas, including the case of only one receive antenna.

A new signal process based on a nonlinear local prediction model (NLLP) is presented and applied to speech coding. With the same implementation, the speech coding based on the NLLP gives improved performance compared to reference versions of the standard ITU-T G.728 and linear local scheme. The computational efforts for the NLLP analysis does not increase over the conventional linear prediction (LP), and the NLLP supplies better prediction performance over the LP and linear local prediction.