| 1. |
|
|
| 2. |
- Haqiqatnejad, A., et al.
(författare)
-
Constructive Interference for Generic Constellations
- 2018
-
Ingår i: IEEE Signal Processing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1070-9908 .- 1558-2361. ; 25:4, s. 586-590
-
Tidskriftsartikel (refereegranskat)abstract
- In this letter, we investigate optimal and relaxed constructive interference regions (CIR) for the symbol-level pre-coding (SLP) problem in the downlink of a multiuser multiple-input single-output (MISO) channel. We define two types of CIRs, namely, distance preserving CIR (DPCIR) and union bound CIR (UBCIR) for any given constellation shape and size. We then provide a systematic way to describe these regions as convex sets. Using the definitions of DPCIR and UBCIR, we show that the SLP power minimization problem, minimizing either sum or peak (perantenna) transmit power, can always be formulated as a convex optimization problem. Our results indicate that these regions allow further reduction of the transmit power compared to the current state of the art without increasing the computational complexity at the transmitter or receiver.
|
|
| 3. |
|
|
| 4. |
|
|
| 5. |
|
|
| 6. |
- Haqiqatnejad, A., et al.
(författare)
-
Power Minimizer Symbol-Level Precoding : A Closed-Form Suboptimal Solution
- 2018
-
Ingår i: IEEE Signal Processing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1070-9908 .- 1558-2361. ; 25:11, s. 1730-1734
-
Tidskriftsartikel (refereegranskat)abstract
- In this letter, we study the optimal solution of multiuser symbol-level precoding (SLP) for minimization of the total transmit power under given signal-to-interference-plus-noise ratio constraints. Adopting the distance preserving constructive interference regions (DPCIR), we first derive a simplified reformulation of the problem. Then, we analyze the structure of the optimal solution using the Karush-Kuhn-Tucker optimality conditions. This leads us to obtain a closed-form suboptimal SLP solution (CF-SLP) for the original problem. Meanwhile, we obtain the necessary and sufficient condition under which the power minimizer SLP is equivalent to the conventional zero-forcing beamforming (ZFBF). Simulation results show that CF-SLP provides significant gains over ZFBF, while performing quite close to the optimal SLP in scenarios with rather small number of users. The results further indicate that the CF-SLP method has a reduction of order 103 in computational time compared to the optimal solution.
|
|
| 7. |
|
|
| 8. |
- Haqiqatnejad, A., et al.
(författare)
-
Robust SINR-Constrained Symbol-Level Multiuser Precoding with Imperfect Channel Knowledge
- 2020
-
Ingår i: IEEE Transactions on Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-587X .- 1941-0476. ; 68, s. 1837-1852
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we address robust design of symbol-level precoding (SLP) for the downlink of multiuser multiple-input single-output wireless channels, when imperfect channel state information (CSI) is available at the transmitter. In particular, we consider a well known model for the CSI imperfection, namely, stochastic Gaussian-distributed uncertainty. Our design objective is to minimize the total (per-symbol) transmission power subject to constructive interference (CI) constraints as well as the users' quality-of-service requirements in terms of signal-to-interference-plus-noise ratio. Assuming stochastic channel uncertainties, we first define probabilistic CI constraints in order to achieve robustness to statistically known CSI errors. Since these probabilistic constraints are difficult to handle, we resort to their convex approximations in the form of tractable (deterministic) robust constraints. Three convex approximations are obtained based on different conservatism levels, among which one is introduced as a benchmark for comparison. We show that each of our proposed approximations is tighter than the other under specific robustness settings, while both of them always outperform the benchmark. Using the proposed CI constraints, we formulate the robust SLP optimization problem as a second-order cone program. Extensive simulation results are provided to validate our analytic discussions and to make comparisons with conventional block-level robust precoding schemes. We show that the robust design of symbol-level precoder leads to an improved performance in terms of energy efficiency at the cost of increasing the computational complexity by an order of the number of users in the large system limit, compared to its non-robust counterpart.
|
|
| 9. |
- Haqiqatnejad, A., et al.
(författare)
-
Symbol-Level Precoding Design Based on Distance Preserving Constructive Interference Regions
- 2018
-
Ingår i: IEEE Transactions on Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-587X .- 1941-0476. ; 66:22, s. 5817-5832
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we investigate the symbol-level precoding (SLP) design problem in the downlink of a multiuser multiple-input single-output channel. We consider generic two-dimensional constellations with any shape and size, and confine ourselves to one of the main categories of constructive interference regions (CIR), namely distance preserving CIR (DPCIR). We provide a comprehensive study of DPCIRs and derive several properties for these regions. Using these properties, we first show that any signal in a given DPCIR has a norm greater than or equal to the norm of the corresponding constellation point if and only if the convex hull of the constellation contains the origin. It is followed by proving that the power of the noise-free received signal in a DPCIR is a monotonic strictly increasing function of two parameters relating to the infinite Voronoi edges. Using the convex description of DPCIRs and their characteristics, we formulate two design problems, namely the SLP power minimization with signal-to-interference-plus-noise ratio (SINR) constraints, and the SLP SINR balancing problem under max-min fairness criterion. The SLP power minimization based on DPCIRs can straightforwardly be written as a quadratic programming. We derive a simplified reformulation of this problem, which is less computationally complex. The SLP max-min SINR, however, is non-convex in its original form, and hence difficult to tackle. We propose alternative optimization approaches, including semidefinite programming formulation and block coordinate descent optimization. We discuss and evaluate the loss due to the proposed alternative methods through extensive simulation results.
|
|
| 10. |
|
|
