High Efficiency Cooperative Coding And Massive MIMO Technologies

In the future information society, in order to satisfy the ever-increasing demands from wireless data services, high speed and reliable communication services should be provided by the next generation wireless networks. Thus, one of the key challenges is to largely improve the spectral efficiency. Using cooperative coding, the space and frequency resources can be fully ultilzied by the cooperation of the nodes in the network; employing massive multiple input multiple output(MIMO) technologies, the effects of user-interference, fast fading and inter-cell interfence will be reduced by increasing the number of base station antennas. The above protocols can bring large improvement on the spectral efficiency, as well as great challgenes on the system design. This thesis focuses on the protocol design, performance analysis and parameter optimation for cooperative coding and massive MIMO techonogies. The main novelties and contributions are listed as follows:1. Based on joint interference-cancellation and maximum-ratio-combining(IC-MRC) detection algorithm, a superposition-coding(SC)-based transmission scheme is proposed. To verify the efficiency of the scheme, closed-form expressions and upper bounds of the bit error probability(BEP) are derived. A downlink coordinated two-point(DCTP) system is considered, where two users receive the information from two base stations. Compared with the classic SC(CSC) detector, an IC-MRC detection algorithm is proposed, which reduces the error probability of the system. Closed-form expressions of the BEP of the proposed scheme are derived. Under the same power and time constraint, a signal-to-noise ratio(SNR) gain is obtained by employing the SC scheme. Tight upper bounds of the BEP are derived to provide insight, based on which optimal power allocation is also derived to optimize the system performance in terms of the BEP.2. A binary multiuser network coding(BMNC) scheme is proposed in the multiway relay networks. The closed-form expressions and upper bound of the symbol error probability(SEP) are derived, as well as the optimal network coding(NC) matrix. A multiuser multiway relay networks is considered, where N user nodes exchange their information through a single-relay node. Due to the limitation of complexity, we only consider the BMNC in the relay to increase the throughput. The BMNC matrix [in GF(2)] is studied and several design criteria on the BMNC matrix are proposed to improve the SEP performance. Closed-form expressions of the SEP of the system are provided, as well as an upper bound of the SEP, which is proposed to provide further insights into system performance. We then design BMNC matrices to minimize error probabilities.3. Protocol design, performance analysis, and design optimization of space-time network coding(STNC) are proposed, under the Nakagami-m fading channels. The symbol error rate(SER) of STNC is analyzed in a distributed cooperative network over independent but not necessarily identically distributed(i.n.i.d.) Nakagami-m fading channels. In considered network, with the assistance of multiple decode-and-forward(DF) relays, multiple sources communicate with a single destination. New exact closed-form expressions are derived for the SER with M-ary phase-shift keying modulation(M-PSK) and M-ary quadrature-amplitude modulation(M-QAM). Then in the high signal-to-noise ratio(SNR) regime, new compact expressions for the asymptotic SER are derived to offer valuable insights into the network behavior. Importantly, we demonstrate that STNC guarantees full diversity order, which is determined by the Nakagami-m fading parameters of all the channels but independent of the number of sources. Based on the new expressions, we examine the impact of the number of relays, relay location, Nakagami-m fading parameters, power allocation, and nonorthogonal codes on the SER.4. For of a large uplink multi-user MIMO system, the effects of large-scale fading on the ergodic achievable rate are analyzed. Generalized-K fading channels are employed. In the considered scenario, multiple users transmit their information to a base station, which is equipped with a very large number of antennas. Since the effect of fast fading asymptotically disappears in massive MIMO systems, large-scale fading becomes the most dominant factor for the ergodic achievable rate of massive MIMO systems. Regarding this fact, in our work we concentrate our attention on the effects of large-scale fading for massive MIMO systems. Specifically, some interesting and novel asymptotic expressions of ergodic achievable rate have been derived with both perfect channel state information(CSI) and imperfect CSI. Simulation results assess the accuracy of these analytical expressions.5. For the uplink of a single-cell multi-user distributed massive MIMO system, some userful expressions of the achievable rate is proposed, based on which the antenna location is optimaized. In the considered scenario, 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.