Research On The Technologies Of Interference Alignment And Interference Management For B4G/5G Wireless Networks

Due to the popularity of social networks and smart mobile device, the mobile data traffic will be ex-plosive growth for the years to come. Meanwhile, low energy consumption and wide coverage is also the development needs for of the future B4G/5G wireless networks. However, the currently 4G technology has not been able to meet these needs. To satisfy these requirements, the future wireless network architecture is moving towards multi-layer networks fusion. Although such overlay dense networks hold great promise for achieving higher capacity and wider coverage in dense areas, the overlay dense networks have extremely complex topological structure, and coexistence of multiple layer networks in the same coverage area makes interference management a significant issue, which leads to more complex interference structure compared to 4G networks. To address these problems, technologies such as interference alignment, cognitive cooperative interference alignment and green interference coordination and so on are supposed to introduced. This the-sis focused on the effective transmission scheme of interference alignment and interference management for B4G/5G wireless networks. For interference channels, multicell broadcast interfering channels and cognitive radio networks, the research of the thesis includes the transmission scheme based on hierarchy interference alignment for multicell MU-MIMO wireless networks, the transmission schemes in cognitive MIMO inter-ference alignment network without transmitter cooperation, the transceiver design for cognitive interference alignment networks with transceiver cooperation, the robust transceiver design based on interference align-ment with adjustable weight, non-linear energy efficiency optimization in the multicell MIMO broadcast channel with interference coordination and resource efficiency optimization with interference coordination. The main contributions of this thesis are listed as follows:1. We investigate a hierarchy interference alignment approach for a network with multiple cells and MIMO users under a MIMO interfering broadcast channel scenario. Based on that, a new general interference alignment scheme is proposed. Next, to improve the performance of the general interference alignment scheme at medium-to-low SNR, we propose a new hierarchy transceiver design algorithm by minimizing the sum weighted mean square error subject to per-base station power constraints. From simulations, it is observed that the proposed schemes can greatly reduce the interference. Also, we confirm that our later scheme outperforms the conventional schemes in medium-to-low SNR regime.2. Applying Bezout theorem, we derive the cognitive interference alignment feasibility conditions that allows multiple secondary users to access the same frequency band of a pre-existing primary user link without cooperative transceiver. Based on that, an iterative subspace-based cognitive interference alignment algo-rithm is also presented that lease the assumption of channel reciprocity. However, the proposed subspace-based assumes that each data stream of secondary users employs identical transmit power,which means there are always some leftover interference signal in the desired signal subspace of secondary users. To address this problem, we present an improved subspace-based cognitive interference alignment scheme, which combines our proposed subspace cognitive interference alignment algorithm and the power allo-cation strategy between data streams of the secondary users. From the simulations, we confirm that our proposed algorithms provide a substantial performance gain over the conventional cognitive interference alignment scheme.3. The cognitive interference alignment is investigated in dense aware networks including multiple primary user links and secondary user links with transmitter cooperation. A new cognitive interference alignment feasibility conditions with cooperative transmitter and and a new upper bound of degree of freedom is deduced. Meanwhile, an iterative algorithm is also proposed that utilizes channel reciprocity to verify the effectiveness and rationality of the new bound. Analytical results and simulations both show that the new DoF bound of the proposed cognitive interference alignment with transmitter cooperation is higher than or at least equal to that of the cognitive interference alignment. Also, we can confirm that the primary trans-mitters’participation in secondary users’interference alignment significantly increases both the secondary and total rate with negligible primary rate reduction.4. We investigate robust interference alignment transceiver designs for K-users MIMO interference channel-s while taking imperfect channel knowledge into consideration. Under the assumption of norm-bounded channel uncertainties, the proposed robust transmission scheme aims to minimize the interference signal that leak into the desired signal subspace and makes the desired signal fall into the desired signal subspace subject to identical transmit power between data streams. Using the iterative technology, the original optimization problem is divided into two stages sub-problem, which update the precoder matrix and in-terference subspace matrix via Rayleigh-Ritz theorem. Finally, an iterative robust transceiver based on interference alignment with adjustable weight is proposed. From the simulations, we demonstrate that our proposed robust transmission scheme offers not only better sum rate performance but also higher robust-ness against imperfect channel knowledge than the conventional algorithm.5. We investigate the non-linear precoding design to maximize the sum weighted energy efficiency in a mul-ticell MIMO broadcast channel with interference coordination. To address this non-convex optimization problem, we propose to first transform the original problem into a polynomial form optimization with the aid of classical Arimoto-Blahut algorithm and fractional programming theory. Then, the optimization problem is solved with Lagrange optimization theory. Finally, the the energy efficiency optimization algo-rithm with dirty paper code is proposed. The simulation results demonstrate that, compared to the existing linear energy efficiency optimization algorithm, the proposed algorithm is superior due to the dirty paper coding technology.6. We investigate the transmission scheme design to maximize the sum resource efficiency in a multicell MI-MO broadcast channel with interference coordination. The resource efficiency is defined as the weighted sum of spectral efficiency and energy efficiency to achieve reasonable tradeoff between two conventional metrics. In order to solve this intractable non-convex problem, we first equivalently transform the original problem into a parameterized subtractive form optimization problem via classical Arimoto-Blahut algo-rithm and fractional programming theory. Based on that, we solve the equivalent problem according to Lagrange optimization theory. Finally, an effective algorithm is presented to obtain the solution to the considered resource efficiency optimization. Extensive simulation results is provided to verify the effec-tiveness of our algorithm. Also, the numerical simulations give the corresponding performance analysis and comparison.